untitled A population-based study of KCNH7 p.Arg394His and bipolar spectrum disorder Kevin A. Strauss1,2,3,{,∗, Sander Markx4,{, Benjamin Georgi5, Steven M. Paul7, Robert N. Jinks8, Toshinori Hoshi6, Ann McDonald4, Michael B. First4, Wencheng Liu7, Abigail R. Benkert1,8, Adam D. Heaps1, Yutao Tian6, Aravinda Chakravarti9, Maja Bucan5 and Erik G. Puffenberger1,2, { 1 Clinic for Special Children, Strasburg, PA, USA, 2 Franklin & Marshall College, Lancaster, PA, USA, 3 Lancaster General Hospital, Lancaster, PA, USA, 4Department of Psychiatry, Columbia University, New York, New York, USA, 5Department of Genetics, Perelman School of Medicine and, 6Department of Physiology, University of Pennsylvania, Philadelphia, PA, USA, 7 Departments of Neuroscience, Psychiatry and Pharmacology, Weill Cornell Medical College of Cornell University, New York, New York, USA, 8Biological Foundations of Behavior Program, Franklin & Marshall College, Lancaster, PA, USA and 9Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA Received February 4, 2014; Revised and Accepted June 25, 2014 We conducted blinded psychiatric assessments of 26 Amish subjects (52 +++++ 11 years) from four families with prevalent bipolar spectrum disorder, identified 10 potentially pathogenic alleles by exome sequencing, tested association of these alleles with clinical diagnoses in the larger Amish Study of Major Affective Disorder (ASMAD) cohort, and studied mutant potassium channels in neurons. Fourteen of 26 Amish had bipolar spec- trum disorder. The only candidate allele shared among them was rs78247304, a non-synonymous variant of KCNH7 (c.1181G>A, p.Arg394His). KCNH7 c.1181G>A and nine other potentially pathogenic variants were sub- sequently tested within the ASMAD cohort, which consisted of 340 subjects grouped into controls subjects and affected subjects from overlapping clinical categories (bipolar 1 disorder, bipolar spectrum disorder and any major affective disorder). KCNH7 c.1181G>A had the highest enrichment among individuals with bipolar spec- trum disorder (x2 5 7.3) and the strongest family-based association with bipolar 1 (P 5 0.021), bipolar spectrum (P 5 0.031) and any major affective disorder (P 5 0.016). In vitro, the p.Arg394His substitution allowed normal expression, trafficking, assembly and localization of HERG3/Kv11.3 channels, but altered the steady-state volt- age dependence and kinetics of activation in neuronal cells. Although our genome-wide statistical results do not alone prove association, cumulative evidence from multiple independent sources (parallel genome-wide study cohorts, pharmacological studies of HERG-type potassium channels, electrophysiological data) implicates neuronal HERG3/Kv11.3 potassium channels in the pathophysiology of bipolar spectrum disorder. Such a find- ing, if corroborated by future studies, has implications for mental health services among the Amish, as well as development of drugs that specifically target HERG3/Kv11.3. INTRODUCTION Mental illness afflicts 12 – 49% of people worldwide (1). Mood disorders—including bipolar 1 disorder, bipolar spectrum dis- order and major depressive illness—account for at least half of this global mental health burden (2). In North America, 40% of medical disability in persons aged 15 – 44 years is attributable to psychiatric illness (2) and in the USA, suicides outnumber homicides two to one (3). Our failure to prevent serious psychi- atric morbidity results in part from insufficient understanding of † Equal contributors. ∗ To whom correspondence should be addressed at: Clinic for Special Children, 535 Bunker Hill Road, Strasburg PA, 17579, USA. Tel: +1 7176879407; Fax: +1 7176879237; Email: kstrauss@clinicforspecialchildren.org # The Author 2014. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/ .0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Human Molecular Genetics, 2014, Vol. 23, No. 23 6395–6406 doi:10.1093/hmg/ddu335 Advance Access published on June 30, 2014 4 http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/ its root causes (4). Here, the application of genetics holds promise as a means to identify individuals predisposed to psychi- atric disease (5), but genetic studies of mental illness have thus far produced few specific risk alleles that help clinicians care for patients (6). The Clinic for Special Children (CSC) is a non-profit commu- nity health center that serves uninsured Amish and Mennonite (Plain) communities of Pennsylvania (USA) and surrounding states (7). Although the CSC has historically focused on pediat- ric health, bipolar and other affective disorders pervade every aspect of family and community life (8) and it is increasingly ap- parent that adult-onset mental disorders can be associated with prodromal symptoms during childhood, including disturbances of mood, attention and thought (9). The CSC invests heavily in genetic strategies that allow prevention of disability and disease (7). This concept is germane to the diagnosis and treat- ment of mental disorders, for which early detection of specific risk alleles in youth could enable more timely and effective psy- chiatric care (5). Endogamous populations such as the Old Order Amish provide distinct advantages for investigating the genetic bases of mental illness (10,11). The Amish Study of Major Affective Disorder (ASMAD), initiated in 1976 by Egeland and collea- gues, has tracked several large, multi-generation pedigrees with high prevalence of bipolar spectrum disorders (12). Despite three decades of sustained and valuable research, the ASMAD cohort has revealed no definitive genetic risk factors for major affective disease (13). However, a recent study of ASMAD subjects (N ¼ 388) that combines microsatellite and high-density single nucleotide polymorphism (SNP) geno- types with whole-genome sequence data implicates dozens of rare alleles that may interact to determine risk for bipolar disorder (14). Traditional linkage analysis is less informative in the ASMAD cohort given multiple, unexpected lines of interrelatedness within an endogamous group such as the Amish (13). Mapping susceptibility alleles for mental disorders in any population poses additional challenges: (a) behavioral phenotypes such as bipolar disorder are, by their nature, incompletely penetrant and variable in expression both within and between individuals; (b) a single genetic variant can have pleiotropic effects on psychopathology that change over the lifespan (15,16); (c) cat- egorization of mental illness often depends critically on self- reporting of remembered subjective experience, vulnerable to errors of both omission and commission; and (4) instruments currently used to categorize mental disorders (e.g. Diagnostic and Statistical Manual of Mental Disorders, DSM) are based on phenomenology rather than firm biological constructs (17,18), and thus do not capture the full phenotypic spectrum (i.e. endophenotypes) associated with any particular susceptibil- ity allele (4,19,20). These facts are especially problematic when using conven- tional statistical paradigms to identify rare variants of clinical significance in small, endogamous groups (11). Recognizing this, we developed a strategy that depends on multiple, conver- ging lines of evidence to evaluate a complex phenotype within a narrow genetic context. We first applied an approach common- ly used to investigate Mendelian disorders (10,21), searching whole-exome data for low-frequency alleles shared among closely related Amish individuals with bipolar spectrum disorder (11,13). We then used these findings to independently test for genetic associations within the larger ASMAD cohort (14), and finally conducted functional studies of mutant potas- sium channels in neuronal cells. Based on our statistical and functional results, KCNH7 c.1181G.A (p.Arg394His; rs78247304) emerges as a strong candidate for bipolar disease risk among the Pennsylvania Amish. This corroborates findings from a recent genome-wide association (GWA) study of an independent cohort of Taiwanese patients, which isolated KCNH7 as one among four genes likely to be associated with bipolar 1 disorder (22). To support the genetic data, we provide functional evidence that p.Arg394His alters the electrophysiological properties of HERG3/Kv11.3-mediated po- tassium currents in neuronal cells. Taken together, these findings suggest that functional variation of HERG-type neuronal potas- sium channels (19 – 21), and HERG3/Kv11.3 in particular, may have a role in the pathogenesis of bipolar disorder and schizophre- nia. Because our association data do not reach genome-wide sig- nificance, the main finding should be viewed as provisional until confirmed or refuted by future studies. RESULTS Exome variants in core Amish families A – D We initially studied four Old Order Amish sibships with a high prevalence of bipolar disorder (Fig. 1). Families A – D consisted of 26 Amish subjects (mean age 52 + 11 years, range 34 – 79 years, 58% female) who underwent independent, blinded psy- chiatric assessment. Phenotype was characterized on four levels (Table 1): (1) Structured Clinical Interview for DSM-IV-TR (SCID) diagnosis; (2) a sub-categorization of de- pressive, manic and psychotic symptom clusters; (3) a designa- tion of multidomain affected if at least two of three symptom clusters (i.e. mania, depression and psychosis) were present; and (4) a detailed breakdown of specific symptoms (Supplemen- tary Material, Table S1). Fourteen of 26 Amish subjects from Families A – D (Fig. 1) met DSM-IV-TR criteria for at least two of three symptom clus- ters (mania, depression or psychosis) and were designated as multidomain affected. They comprised diverse Axis 1 diagnoses (Table 1 and Supplementary Material, Table S1): bipolar 1 with psychotic features (N ¼ 6), bipolar 2 with psychotic features (N ¼ 1), bipolar disorder not otherwise specified (N ¼ 3), schizoaffective disorder (N ¼ 2), schizophrenia with major de- pressive disorder (N ¼ 1), and recurrent major depression com- plicated by somatoform disorder and substance-induced psychosis (N ¼ 1). Seven of these 14 subjects were chosen for exome sequencing (indicated with asterisks in Fig. 1) and shared a total of 17 609 exome variants. Because our study design lacked power to detect common var- iants associated with small or modest effects, we restricted our focus to low-frequency variants with potentially higher patho- genicity (Fig. 2). We first excluded alleles with minor allele fre- quency .10% in control Plain exomes; this narrowed the list to 35 variants. We then excluded synonymous and intronic changes which further reduced the number to 10 ‘candidate’ variants (Table 2 and Fig. 2). To perform association analyses, all 26 sub- jects from Families A – D and all 340 subjects from the ASMAD cohort were genotyped for these 10 variants (Figs 1. and 2). 6396 Human Molecular Genetics, 2014, Vol. 23, No. 23 http://creativecommons.org/licenses/by-nc/3.0/ http://creativecommons.org/licenses/by-nc/3.0/ http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 Candidate variants in three of 10 genes (KRT75, UTP14C, NEK5) had minor allele frequencies .10% in 1000 Genomes Project, European controls, or the Exome Variant Server. Among variants in the 7 genes, three (KCNH7, MUC4, ALDH9A1) were predicted to be pathogenic by SIFT, PolyPhen-2 and Mutation Taster, and two of these (KCNH7, MUC4) were absent in all three non-Plain control exome datasets (1000 Genomes Project, European controls, Exome Variant Server; Table 2). MUC4 p.Cys1309Phe was not associated with bipolar disorder in the ASMAD pedigree [family- based association test (FBAT) P-value ¼ 0.965]. Moreover, mucin-4 has no known function in neurons and is not expressed in human brain (http://proteinatlas.org/). The MUC4 variant was there- fore considered an unlikely candidate. Association of KCNH7 c.1181G>A with psychiatric illness in the ASMAD cohort KCNH7 c.1181G.A (rs78247304) was the only candidate exome variant carried by all 14 subjects from Families A – D who were multidomain affected based on the presence of at least two of three symptom clusters (i.e. mania, depression and psychosis) (Table 1 and Supplementary Material, Table S1). Moreover, KCNH7 c.1181G.A was deemed the most likely pathogenic variant based on multiple converging lines of evidence, including: (a) results from independent GWA and whole-genome sequencing studies (14,22); (b) expression pattern of KCNH7 in areas of the brain that are believed to mediate mood and cognition (23); Figure 1. A (Upper panel): 26 individuals from four families underwent blinded, independent psychiatric assessments using the Structured Clinical Interview for DSM-IV (SCID), Research Version. Exome sequencing was done on subjects designated with a red asterisk. Families A – C (blue enclosures) were interviewed during the first phase of the study and Family D (green enclosure) was recruited later. Black symbols indicate individuals who met DSM-IV-TR criteria for at least two of three symptom clusters—mania, major depression, psychosis—and were considered multidomain affected with bipolar spectrum disorder. Gray symbols indicate individuals who met diagnostic criteria for depressive illness (recurrent or single episode) uncomplicated by mania or psychosis. The ‘‡’symbol indicates subjects who were unavailable for interviews or declined to participate. B (Lower panel): during the second phase of the study, 340 samples from the ASMAD were used to test associations of exome variants with bipolar spectrum disorder (eighteen ASMAD samples were individuals from Families A and C and thus excluded from the replication analysis). All ASMAD subjects were genotyped for 10 candidate exome variants and categorized as unaffected (N ¼ 247) or affected (N ¼ 93) by major affective illness; the latter category was then subdivided into the increasingly restrictive designations of bipolar spectrum disorder (N ¼ 78) and bipolar 1 disorder (N ¼ 63). Human Molecular Genetics, 2014, Vol. 23, No. 23 6397 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 (c) evidence that antipsychotic drugs block the HERG3/Kv11.3 channels encoded by KCNH7 (24); (d) the proposed role of other potassium channel subunits in bipolar disorder and schizophrenia (25 – 28); and e) the conservation of nucleotide guanine 1181 , corre- sponding to amino acid arginine 394 , across all species from Homo sapiens to Caenorhabditis elegans (PhyloP 2.61) (Table 2). To further test this observation, we obtained de-identified DNA and clinical data for 394 ASMAD samples. Individuals from aforementioned Families A and C (Fig. 1) were represented in the ASMAD cohort, but were excluded from the replication analysis. Fifty-four ASMAD subjects had minor or incompletely characterized psychiatric phenotypes and were also excluded. We grouped the remaining 340 subjects into the following over- lapping clinical categories, as depicted in Figure 1: bipolar 1 dis- order (N ¼ 63), bipolar spectrum disorder (N ¼ 78, including bipolar 1, bipolar 2 and bipolar disorder not otherwise specified), any major affective disorder (N ¼ 93, including major depres- sive disorder, recurrent), and unaffected by major affective illness (N ¼ 247). Among these 340 individuals, we investigated association of the 10 candidate variants with psychiatric diagno- ses using three complementary methods: (a) a simple x 2 analysis of allele distribution with phenotype; (b) the FBAT, which mea- sures transmission distortion of alternative alleles to affected and unaffected siblings in pedigrees (29) and (c) the efficient mixed- model association expedited method (EMMAX), which controls and corrects for relatedness between subjects (30). KCNH7 c.1181G . A (rs78247304) behaved in a manner dif- ferent from all other variants (Table 3 and Fig. 3). Table 3 lists nominal (uncorrected) x2 calculations as well as FBAT and EMMAX P-values for the 10 candidate exome variants. KCNH7 Table 1. Phenotypes and genotypes of 26 Amish Study Subjects from Families A – D 6398 Human Molecular Genetics, 2014, Vol. 23, No. 23 c.1181G.A had the highest enrichment in subjects with affective disorders (x 2 for bipolar 1 ¼ 4.2; bipolar spectrum ¼ 7.3, any af- fective disorder ¼ 10.2), lowest EMMAX P-value for bipolar 1 and bipolar spectrum disorders (P ¼ 0.013) and lowest FBAT P-value for bipolar 1 (P ¼ 0.021), bipolar spectrum (P ¼ 0.031) and any major affective disorder (P ¼ 0.016) (Table 3 and Fig. 3). The statistical results presented in Table 3 do not alone provide sufficient evidence of association after correcting for multiple tests. We nevertheless pursued KCNH7 c.1181G . A further based on (a) the weight of evidence from multiple sources (14,22 – 24,27,28,31 – 33); (b) recognition that our cohort size and study design lacked power to generate an un- equivocal signal for any true positive association (discussed below); and (c) the important implications that a true positive as- sociation would have for design of preventative mental health services among Amish communities as well as future drug devel- opment for patients with bipolar disorder and related psychiatric disorders. We thus turned to studies of HERG3 Arg394His expres- sion and function in neurons. Expression and function of KCNH7 Arg394His When overexpressed in mouse and human neuroblastoma cells, wild-type and HERG3/Kv11.3 Arg394His potassium channel protein subunits had similar abundance, core and mature glycosylation and localization to the plasma membrane (Fig. 4A – F and Suppl- ementary Material, Fig. S1). Wild-type and Arg394His mixed monomers co-localized in a pattern indistinguishable from that of wild-type proteins alone, suggesting appropriate intracellular traf- ficking and formation of mature heteromers (Supplementary Material, Fig. S1). Depolarization of Neuro-2a cells transfected with wild-type KCNH7 elicited outward currents that progressively diminished in size with depolarization to .20 mV (Fig. 4G), a pattern char- acteristic of HERG/Kv11 channels with fast C-type inactivation (34). In cells transfected with HERG3 Arg394His , the following differences were observed: (a) When currents were normalized to the maximal current size in each cell, fractionally smaller currents were observed through Arg394His channels at a given voltage ,20 mV (Fig. 4I); (b) Greater depolarization was required to elicit currents through the Arg394His channel; the normalized conductance (G/Gmax) curve, proportional to the probability that the channel is open, was shifted �12 mV in the positive direction (Fig. 4J); and (c) Upon depolarization, current kinetics through the Arg394His channel were slower (Fig. 4K), but the deactivation kinetics at a negative voltage were essentially indistinguishable between the two channel types (Fig. 4L). Together, the results suggest that the p.Arg394His muta- tion slows the activation process of HERG3/Kv11.3 channels and thereby shifts the overall voltage dependence of activation in the positive direction. DISCUSSION KCNH7, HERG-type potassium channels and mental illness By studying a few Amish families to search for low-frequency, relatively penetrant bipolar risk alleles, we discovered a specific missense variant of KCNH7 (c.1181G.A) that appears to segregate with bipolar spectrum disorder among a subset of Penn- sylvania Amish families. In our view, the most important conclu- sions to be drawn from our results are that the KCNH7 c.1181G.A allele, uniquely present in all 14 affected patients among the original cohort of 26, clearly distributes in a way differ- ent from all nine other rare and potentially pathogenic exome var- iants tested within the larger ASMAD cohort (Table 3 and Fig. 3), and significantly alters potassium channel currents in neuronal cells. Given the relatively small sample size used and incomplete penetrance of the bipolar spectrum phenotype, the genetic evi- dence is alone insufficient to provide definitive proof of associ- ation. However, we believe KCNH7 c.1181G.A warrants further investigation based on the cumulative weight of evidence from multiple sources, its high degree of specificity, and the poten- tial public health implications for Amish communities. The KCNH7 c.1181G.A variant (rs78247304) was recently highlighted as one of 30 potentially pathogenic missense variants Figure 2. Among seven Amish individuals with bipolar spectrum disorder, we identified a total of 83 668 exome variants, 17 609 of which remained after filtering out synonymous and intronic changes. Focusing on low-frequency alleles with potentially high pathogenicity, we excluded exome variants with minor allele frequency (MAF) .10% among population-specific control exomes. Only 10 of these variants were present in all seven individuals. These 10 ‘candidate’ alleles were then used to test for associations with bipolar spectrum disorder and broader diagnostic categories within the extended core pedigree (Families A – D, N ¼ 26) and the larger ASMAD cohort (N ¼ 340), respectively. Human Molecular Genetics, 2014, Vol. 23, No. 23 6399 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 Table 2. Ten exome variants among the seven affected Amish individuals chosen for exome sequencing Allele frequency Predicted effects on protein function Chr Position Ref Alt dbSNP135 Gene Class Codon change Amino acid change PhyloP score All plain exomes (n ¼ 84) Amish exomes (n ¼ 56) 1000 Genomes EVS CEU SIFT PolyPhen-2 MutationTaster 1 165 648 710 G A rs55725612 ALDH9A1 Missense gCg/gTg A206V 2.51 0.05 0.06 0.01 0.02 . Damaging Probably damaging Disease-causing 2 163 302 901 C T rs78247304 KCNH7 Missense cGc/cAc R394H 2.61 0.05 0.07 . . . Damaging Probably damaging Disease-causing 2 168 115 797 G C rs75758327 XIRP2 Missense aGa/aCa R692T 20.36 0.08 0.07 0.09 0.07 . Tolerated na Polymorphism 3 195 492 191 C A . MUC4 Missense tGt/tTt C1309F 2.19 0.02 0.03 . . . Damaging Probably damaging Polymorphism 12 38 714 929 A G rs61730283 ALG10B Missense Att/Gtt I446V 22.44 0.03 0.04 0.01 0.02 0.10 Tolerated Benign Polymorphism 12 49 312 681 G T rs117646559 CCDC65 Missense Gat/Tat D238Y 1.24 0.03 0.05 0.01 0.01 . Damaging; low confidence Possibly damaging Polymorphism 12 51 457 854 G A rs11542510 CSRNP2 Missense aCg/aTg T436M 0.75 0.01 0.02 0.04 0.01 0.03 Damaging; low confidence Possibly damaging Polymorphism 12 52 827 740 G C rs2232386 KRT75 Missense Ccc/Gcc P117A 0.32 0.07 0.07 0.13 0.11 0.03 Damaging Probably damaging Disease-causing 13 52 603 241 A G rs3742290 UTP14C Missense Act/Gct T101A 20.10 0.08 0.07 0.09 0.12 0.11 Tolerated Benign na 13 52 676 275 T G rs34756139 NEK5 Missense Aaa/Caa K255Q 1.06 0.08 0.07 0.09 0.11 0.11 Damaging Probably damaging Polymorphism The highest PhyloP value is indicated by orange fill. Alleles that were not detected in non-Plain exomes are designated with green fill, and blue fill indicates alleles predicted to have damaging effects on protein function. ASMAD, Amish Study of Major Affective Disorder; CEU, Control European Exomes; EVS, Exome Variant Server. 6 4 0 0 H u m a n M o le c u la r G e n e tic s, 2 0 1 4 , V o l. 2 3 , N o . 2 3 in whole-genome sequence analysis of ASMAD extended fam- ilies (14). A parallel, independent GWA study of Taiwanese patients identified a different KCNH7 variant (rs6736615) as one of four alleles associated with bipolar 1 (empirical P-value ¼ 0.0047; N ¼ 1555) (22). Again, the statistical signal for rs6736615 fell short of genome-wide significance among Tai- wanese patients, but this allele nevertheless behaved in a way not likely to be observed by chance. Available data also implicate other potassium channels genes (KCNH2 and KCNJ3) in bipolar disorder and schizophrenia (27), localize HERG-type channels to the brain’s limbic circuits (33,35), and demonstrate a role for altered potassium currents in mania and the therapeutic actions of lithium (36 – 38). These converging lines of evidence, com- bined with genetic and electrophysiological data detailed in this report, suggest that variation of neuronal HERG-type potassium channels (25 – 27), and specifically HERG3/Kv11.3, might con- tribute to mental illness in certain individuals. KCNH7 and mechanisms of mental illness HERG3/Kv11.3, encoded by KCNH7, belongs to the ether-á- go-go-related (ERG) family of voltage-gated potassium chan- nels expressed throughout the mammalian brain, especially in limbic and cortical areas associated with mood and cognition (35). Heterologously expressed HERG3 Arg394His is processed to the plasma membrane in neuroblastoma cells, but the histidine substitution at a highly conserved cytoplasmic arginine 394 shifts voltage dependence of activation in the positive direction and Table 3. Association testing of 10 exome variants with affective disorders in the ASMAD cohort (N ¼ 340) a Gene Chromosome Variant Bipolar 1 disorder Bipolar spectrum disorder Any major affective disorder x2 FBAT P EMMAX P x2 FBAT P EMMAX P x2 FBAT P EMMAX P ALDH9A1 1 A206V 0.4 0.408 0.224 0.1 0.889 0.303 0.1 0.861 0.968 KCNH7 2 R394H 4.2 0.021 0.174 7.3 0.031 0.013 10.2 0.016 0.189 XIRP2 2 R692T 1.3 0.484 0.465 2.6 0.408 0.113 1.2 0.345 0.882 MUC4 3 C1309F 0.8 0.965 0.670 0.2 0.906 0.356 0.0 0.761 0.919 ALG10B 12 I446V 1.4 0.276 0.194 0.9 0.599 0.651 0.2 0.687 0.774 CCDC65 12 D238Y 0.8 0.514 0.637 0.1 0.751 0.772 0.0 0.683 0.946 CSRNP2 12 T436M 0.2 0.824 0.939 0.1 0.654 0.606 0.5 0.940 0.867 KRT75 12 P117A 0.8 0.405 0.742 1.7 0.366 0.555 3.7 0.227 0.081 UTP14C 13 T101A 0.2 0.349 0.543 0.0 0.722 0.256 0.4 0.613 0.149 NEK5 13 K255Q 0.1 0.349 0.543 0.0 0.722 0.256 0.2 0.613 0.149 a The nominally most significant value from each column is shaded blue (bipolar 1 disorder), red (bipolar spectrum) or purple (any major affective disorder). Figure 3. Testing for the association of 10 rare candidate alleles with bipolar 1 (BP1, circles), bipolar spectrum (BPS, squares), and any major affective disorder (any Aff, triangles) among 340 subjects from the Amish Study of Major Affective Disorder cohort. FBAT P-values (abscissa) and x 2 distribution (ordinate) were calculated for each of the 10 rare candidate gene variants detected by exome sequencing. Nine of these variants (ALDH9A1, XIRP2, MUC4, ALG10B, CCDC65, CSRNP2, KRT75, UTP14C and NEK5) are plotted in gray. KCNH7 c.1181G.A, represented with red symbols, shows the strongest association with affective disorders and shows an unusual distribution behavior among the 10 variants. For graphical clarity, FBAT is transformed to the 2log10; dotted lines indicate arbitrary thresholds of P ≤ 0.5 and X 2 ≥ 4 for FBAT and chi-square testing, respectively. Human Molecular Genetics, 2014, Vol. 23, No. 23 6401 slows activation kinetics; thus the mutation is predicted to increase excitability of neuronal cells in vivo. Penetrance and severity of mental illness were similar among KCNH7 c.1181G.A heterozygotes and homozygotes. This may reflect the heterotetrameric nature of ERG channels (e.g. other ERG subunits may partially substitute for ERG3) and/or a high degree of potassium channel redundancy in the nervous system that attenuates the biological impact of modest functional abnor- malities of any one channel subunit (39). Potassium channel dysfunction appears mechanistically im- portant in animal models of mania and may be relevant to the actions of lithium (32). KCNH7 is expressed in mammalian mid- brain, where its blockade prolongs plateau potentials in bursting dopaminergic neurons and may in turn alter mesolimbic dopa- mine release (31). Certain typical and atypical antipsychotic drugs inhibit HERG3/Kv11.3 (31) and lithium is believed to exert mood-stabilizing effects in part by modulating potassium currents, either by reducing voltage-gated potassium channel open events or by inhibiting GSK3ß kinase-mediated channel phosphorylation (37). In murine models of mania (KCND2/ Kv4.2 knockout; ClockD19), genetic deletion or experimental manipulation of potassium currents attenuates physiological and behavioral correlates of mania and dose-dependently increases phosphorylation of GSK3b in prefrontal cortex and hippocampus (36). The latter mechanism is thought to be shared among all effective mood-stabilizing drugs (35). Figure 4. Left panel: localization of overexpressed KCNH7 wild-type and Arg394His in Neuro-2a cells immunostained under non-permeabilizing conditions (see Materials and Methods) with mouse monoclonal anti-V5 IgG2a (1:500), followed by AlexaFluor 488-conjugated goat anti-mouse IgG2a (1:400). Nuclei were stained with 4’,6-diamidino-2-phenylindole (DAPI, 1.5 mg/ml) (blue fluorescent signal). (A and B) KCNH7 wild-type and Arg394His with the V5 epitope tag inserted in the S1 – S2 extracellular loop localize to the plasma membrane in non-permeabilized Neuro-2a cells (single confocal images). (C and D) Maximum projection z-stack images of the cells shown in A and B. (E) Left—confocal image of Neuro-2a cells transiently overexpressing Arg394His S1-V5-S2-KCNH7. Right—Orthogonal projection of a section through the cell in the center of the left image demonstrating membrane localization for Arg394His S1-V5-S2-KCNH7. (F) Western blot of transiently overexpressed wild-type and Arg394His S1-V5-S2-KCNH7 fusion proteins in Neuro-2a cells from the same transfections used for A – D. S1-V5-S2-KCNH7 fusion proteins migrated as a core glycosylated and mature glycosylated doublet at �140 kDa. b-Actin was labeled as a loading control. Primary antibodies: anti-V5 mouse monoclonal IgG2a (1:5000) and anti-b actin (1:1 000 000). Secondary antibody: goat anti-mouse IgG HRP-conjugated (1:1500). Data are representative of four independent transfections. Right panel: electrophysiological characteristics of wild-type (WT) and Arg394His HERG3 (KCNH7) currents. (G) Representative currents from a Neuro-2a cell transiently expressing WT HERG3 channels. (H) Representative currents from a Neuro-2a cell transiently expressing Arg394His HERG3 channels. (I) Scaled peak current – voltage (I/Imax) curves for WT (blue) and Arg394His (red) channels. The results are normalized to the maximal current size in each cell. The data points are connected by lines for an illustrative purpose only. n ¼ 12 and 9 for WT and Arg394His, respectively. (J) Normalized conductance (G/Gmax) as a function of voltage for WT (blue) and Arg394His (red). The half-activation voltage (V0.5) and the apparent equivalent charge movement were – 7.5 + 1.1 mV and 4.7 + 0.53e0 for WT and 4.5 + 1.1 mV and 3.8 + 0.50e0 for Arg394His. n ¼ 12 and 9 for WT and Arg394His, respectively. The V0.5 values for Arg394His are statistically different from those for WT (P , 1 × 10 – 5). The equivalent charge numbers are indistinguishable between the groups (P ¼ 0. 129). The smooth curves are Boltzmann fits to the pooled results. Kinetics of ionic currents at 20 mV (K) and – 120 mV (L). Currents are scaled to facilitate comparison. The sweep width represents the mean + SEM. In (K), n ¼ 7 and 8 for WT and Arg394His, respectively. In (L), n ¼ 5 and 4 for WT and Arg394His, respectively. 6402 Human Molecular Genetics, 2014, Vol. 23, No. 23 A community-based approach to psychiatric genetics Among people afflicted with serious mental disorders, conserva- tive estimates suggest that only 50 – 65% in developed nations and 15 – 24% in less-developed nations are diagnosed and treated appropriately (1). Such is the case in Amish communities (8), where treatment for psychiatric disease may only occur in re- sponse to crises like intractable mental anguish, emergent hospi- talization, violence, or the threat of suicide (8). The treatment gap (1) in Amish as well as other communities results from mul- tiple factors, including social stigma, a dire shortage of profes- sional resources and abiding ignorance of underlying disease mechanisms and their developmental expression (4). For many patients, the first signs of mental illness surface during childhood or adolescence, while there remains a window for effective intervention (4). At present, identification of presymptomatic individuals who might later develop major psychiatric disease is based on a combination of family history, prodromal symptoms, and concerning patterns of behavior (5). Underlying this effort is the simple notion that recognizing a predilection for mental illness allows medical and psychosocial interventions to be implemented proactively (5). Indeed, in- formed prevention has proven the key practical benefit that genetic knowledge confers on clinical practice (10), and it is widely believed that mental health services can be improved by a firmer grounding in genetics and developmental biology (4). Effective treatment strategies for bipolar disorder will largely depend on the identification of biological markers suffi- ciently specific to determine who is at risk (6). The CSC has invested heavily in the discovery of such markers—typically rare and highly penetrant alleles—that can guide the design of population-specific surveillance and prevention programs (7). Despite the presumed genetic complexity of bipolar disorder (40), we hypothesized that one or more rare alleles might exert strong pathogenic effects within certain endogamous demes (13). This strategy allowed us to identify KCNH7 c.1181G.A as a potential risk factor for bipolar spectrum disorder within a subgroup of Pennsylvania Amish families. Population-specific risk alleles and overlapping psychiatric phenotypes Our observations suggest that KCNH7 c.1181G.A, and pre- sumably other psychiatric risk alleles, can have pleiotropic effects and do not segregate solely with a single categorical psychiatric phenotype (e.g. bipolar 1 disorder). KCNH7 c.1181G.A carriers have prevalent psychotic symptoms and diverse, overlapping Axis 1 diagnoses (including schizoaffective disorder, schizophre- nia and major depression). This is not particularly surprising; within the general population, most mental disorders are thought to arise from the combinatorial effects of multiple alleles and their interaction with epigenetic and life events (4). It is also in- creasingly evident that a single allele can segregate with different categorical psychiatric diagnoses (e.g. bipolar disorder or schizo- phrenia) (26,41). This basic model surely also applies to genetic isolates like the Amish, but within such populations it is compara- tively easier to identify low-frequency alleles with stronger pathogenic effects and to document the full range of psychiatric phenotypes that segregate with a particular allele within extended families (21). In the ASMAD cohort, KCNH7 c.1181G.A segregates in 31 nuclear families and is found in 32% of patients with a bipolar spectrum diagnosis. However, within these families it appears to be relatively penetrant and might therefore be clinically ac- tionable (7). Further research is needed to verify this, delineate what other alleles may predispose Amish individuals to mental illness, map their distribution among the various Amish demes, and determine how they might interact with KCNH7 c.1181G.A to affect disease expression. Such knowledge could lead to personalized pharmacological therapies and, for the first time within this community, preventative mental health care (5). Conclusions, limitations and future directions Major limitations of the present study are its small size and narrow focus. By restricting our analysis to Amish cohorts, we may have identified a variant unique to this population. However, a recent independent GWA study suggests an associ- ation between bipolar illness and a different KCNH7 variant in a cohort of ethnically homogeneous Taiwanese patients (22). Observations from Amish and Taiwanese cohorts reveal how we might advance the field of complex disease genetics through the investigation of ‘common’ phenotypes in relatively small, en- dogamous groups (13,42). An association between KCNH7 c.1181G.A and bipolar spectrum disorder, even if limited to a few genetic isolates, informs the underlying biology of mood regulation and can suggest more widely applicable treatment strat- egies (i.e. new drug targets). For certain rare pathogenic alleles discovered in small, isolated populations, conventional statistical thresholds for genome-wide significance may be difficult if not impossible to achieve. For example, a recent review suggests that studies sufficiently powered to identify rare variants of clinical significance should include discovery sets of 25 000 cases or more (11), a number representing roughly half the Amish population of Pennsylvania (42). Moreover, the Pennsylvania Old Order Amish are more accurately understood as many separate founder populations; the several reproductively isolated demes within the state are defined by different allele distributions (10). Germane to this point, KCNH7 c.1181G.A only segregated in a minority of the 72 nuclear families within the ASMAD cohort, and therefore will be only one of many bipolar risk alleles within the population as a whole. These considerations underscore the importance of using mul- tiple or different sources of evidence to optimize investigations of complex and incompletely penetrant phenotypes within small genetic isolates. Despite limitations inherent in the genetic data, we pursued KCNH7 c.1181G.A further for three reasons. First, this allele segregated differently from nine other rare, potentially pathogenic variants in two Amish cohorts (core families A-D and the larger ASMAD pedigree); while recognizing this result could be by chance, we were persuaded by the nominal differences represented in Table 3 and Figure 3. Second, potassium channels in general, and HERG3 channels in particular, have a plausible causative role in bipolar spectrum based on a large body of knowledge about their function in neurons (31,33), distribution within the central nervous system (23), and pharmacological interactions with lithium and antipsychotic drugs (24,36,38). Finally, our interest in KCNH7 c.1181G.A was strengthened Human Molecular Genetics, 2014, Vol. 23, No. 23 6403 by the recent finding of a potential association between KCNH7 and bipolar 1 illness in an independent Taiwanese cohort (22), although the latter study also only demonstrated nominal, not genome-wide, significance (empirical P value ¼ 0.0047; N ¼ 1555). Our observations, together with the evidence for genetic heterogeneity from analysis of whole-genome sequence and imputed genotypes of ASMAD extended families (14), sets the stage for a diverse genetic landscape of bipolar disease risk even within a population as seemingly ‘uniform’ as the Pennsyl- vania Amish (2,43). Moreover, this study highlights the chal- lenges of statistical analyses using small, endogamous groups to study a phenotype that is: (a) incompletely penetrant, (b) vari- able in expression and (c) by its very nature, difficult to categor- ize with certainty. Nevertheless, efforts to link genetic variants to bipolar illness will continue at a rapid pace (4). Our experience suggests that future studies should better delineate subtypes of this complex behavioral disorder by combining systematic discovery of genetic variants with multisystem analyses of quantitative traits that more deeply and reliably characterize the psychopathology (20), and will likely rely on convergent evidence from multiple sources. Multidimensional research strategies within small founder populations could be crucial to these efforts. MATERIALS AND METHODS Phenotypic assessments The study was approved by the Institutional Review Board of Lancaster General Hospital and all patients consented in writing to participate. Study subjects underwent independent, blinded psychiatric assessment using the Structured Clinical Interview for DSM-IV-TR (SCID), Research Version (http:// scid4.org/) (43). For each subject, supplemental information was collected from at least two closely related individuals (e.g. parent, sibling or child) and in some cases, hospital records. Phenotype was characterized on four levels as described above, and phenotypic assessments, including final SCID DSM-IV-TR diagnoses, were determined by uniform consensus among three blinded interviewers (A.M., M.F., S.M.). The ASMAD began in 1976 (44). A five-member psychiatric board blinded to familial ties, pre-existing diagnoses and treat- ment used strict Research Diagnostic and DSM-III/IV criteria to develop consensus diagnoses for each subject. Uniform as- sessment procedures were applied longitudinally for more than three decades of follow-up, and samples were donated to the Coriell Cell Repository (Coriell Institute for Medical Research, Camden NJ). Genomic and statistical methods We performed exome sequencing on a subgroup of 7 Amish sub- jects as previously described (Broad Institute, Boston, MA) (21). Our aim was to identify low-frequency alleles with relatively high penetrance; thus exome data were filtered to exclude syn- onymous and intronic changes as well as variants with minor allele frequency .10% in two different, but overlapping, sets of population control exomes (designated ‘Plain’ exomes: 84 control Amish and Mennonite exomes combined and 56 control Amish exomes). Ten candidate variants passed filtering criteria and were verified by Sanger sequencing (Table 2). For each variant, we obtained a measure of conservation (PhyloP) from the University of California Santa Cruz Genome Browser (http://genome.ucsc.edu/) and modeled potentially damaging effects on protein structure in silico using SIFT (http://sift.jcvi. org/), PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) and MutationTaster (http://mutationtaster.org/). ASMAD samples (N ¼ 340) were genotyped using the Illu- mina Omni 2.5 SNP array platform. In addition, all samples were genotyped for each of the 10 candidate variants using high- resolution melt analysis (LightScanner 32, BioFire Diagnostics; LightCycler 480, Roche Diagnostics). Estimates of pair-wise relatedness of the 340 ASMAD subjects were obtained based on Illumina Omni 2.5 SNP array data. A x2 statistic was used to assess distribution of 10 candidate alleles among individuals with and without mood disorders, and association of these variants with psychiatric diagnoses was tested using the FBAT (29) and ef- ficient mixed-model association expedited (EMMAX) methods (30). The Bonferroni correction was applied for multiple com- parisons. FBAT P-values were 2log10 transformed to construct Figure 3. Functional studies of KCNH7 Arg394His in cell lines All cell lines were obtained from American Type Culture Collection (http://atcc.org/). We cloned wild-type KCNH7 (also known as HERG3 or Kv11.3; NM_033272.3) from human adherent retinal pigment epithelium cells (ARPE-19), introduced c.1181G.A by site directed mutagenesis, and overexpressed verified constructs in human neuroblastoma (SH-SY5Y), mouse neuroblastoma (Neuro-2a) and transformed human embryonic kidney (HEK-293T) cell lines for immuno- fluorescence and western blotting (Supplementary Methods). To assess membrane localization of KCNH7 subunits, the V5 epitope tag (GKPIPNPLLGLDST) was inserted between amino acids 441 and 442 of the S1-S2 extracellular loop of KCNH7 and indirect immunofluorescence labeling was performed under non-permeabilizing conditions. Briefly, S1-V5-S2 KCNH7 fusion proteins overexpressed in Neuro-2a cells were labeled with mouse monoclonal anti-V5 (1:500) (Life Technologies) at 88C for 25 min in DMEM with 10% fetal bovine serum and washed three times before fixation (see Supplementary Methods for details). Neuro-2a cells overexpressing wild-type or KCNH7 Arg394His (N-terminal epitope tags) were tested by patch-clamp experiments using the whole-cell configuration. We recorded ionic currents at room temperature with an Axopatch 200A amp- lifier (Molecular Devices), elicited currents by 2 s pulses applied every 20 s from a holding potential of 280 mV, and analyzed results using custom routines implemented in Igor Pro (Wave- Metrics) (Supplementary Methods). SUPPLEMENTARY MATERIAL Supplementary Material is available at HMG online. ACKNOWLEDGEMENTS The Clinic for Special Children Board of Directors allowed interviews and genetic studies to be conducted on-site and 6404 Human Molecular Genetics, 2014, Vol. 23, No. 23 http://hmg.oxfordjournals.org/lookup/suppl/doi:10.1093/hmg/ddu335/-/DC1 donated the Clinic’s material and professional resources to the study. Dr Stacey Gabriel and the Biological Samples, Genotyp- ing and Sequencing platform at the Broad Institute (Boston, MA) kindly donated exome sequencing services. Dr Alan Shuldiner of the University of Maryland Amish Research Clinic generously shared control exome data. Amos and Rebecca Smoker assisted with study design and subject recruitment. Donald Kraybill and Jean Endicott provided important cultural context for interpret- ation of SCID data. Dr Sara Hamon provided independent statis- tical analyses and made valuable comments about manuscript content. The authors thank Wade Edris, Penn State College of Medicine for assistance with confocal microscopy. We thank Dr Egeland for her tireless effort to study bipolar disorder in the Old Order Amish of Lancaster County, PA and for her dona- tion of DNA samples to the Coriell. Finally, we are especially in- debted to the individuals afflicted with severe mental illness who agreed to participate in this study. Conflict of Interest statement. None declared. FUNDING S.M.P., W.L., B.G. and M.B. were supported by National Insti- tutes of Health grant RO1-MH-093415-02. T.H. and Y.T. were supported in part by National Institutes of Health grant R01-GM-057654. R.N.J., E.G.P. and K.A.S. were supported by HHMI undergraduate science education awards 52006294 and 52007538. R.N.J. was also supported by the Center for Re- search on Women and Newborn Health, and by ConnectCare3. Funding to pay the Open Access publication charges for this article was provided by the Clinic for Special Children. REFERENCES 1. World Health Organization. (2008) mhGAP: Mental Health Gap Action Programme: scaling up care for mental, neurological and substance use disorders, http://www.who.int/mental_health/mhgap/en/. 2. Insel, T.R. (2009) Disruptive insights in psychiatry: transforming a clinical discipline. J. Clin. Invest., 119, 700 – 705. 3. Hurvitz, K. and Kandi, D. 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Psychiatry, 140, 56 – 61. 6406 Human Molecular Genetics, 2014, Vol. 23, No. 23 << /ASCII85EncodePages false /AllowTransparency false /AutoPositionEPSFiles true /AutoRotatePages /PageByPage /Binding /Left /CalGrayProfile () /CalRGBProfile (sRGB IEC61966-2.1) /CalCMYKProfile (U.S. Web Coated \050SWOP\051 v2) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Warning /CompatibilityLevel 1.5 /CompressObjects /Off /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages false /CreateJobTicket false /DefaultRenderingIntent /Default /DetectBlends true /DetectCurves 0.1000 /ColorConversionStrategy /LeaveColorUnchanged /DoThumbnails false /EmbedAllFonts true /EmbedOpenType false /ParseICCProfilesInComments true /EmbedJobOptions true /DSCReportingLevel 0 /EmitDSCWarnings false /EndPage -1 /ImageMemory 524288 /LockDistillerParams false /MaxSubsetPct 100 /Optimize true /OPM 1 /ParseDSCComments true /ParseDSCCommentsForDocInfo false /PreserveCopyPage true /PreserveDICMYKValues true /PreserveEPSInfo true /PreserveFlatness true /PreserveHalftoneInfo false /PreserveOPIComments true /PreserveOverprintSettings false /StartPage 1 /SubsetFonts true /TransferFunctionInfo /Preserve /UCRandBGInfo /Remove /UsePrologue false /ColorSettingsFile () /AlwaysEmbed [ true ] /NeverEmbed [ true /Courier /Courier-Bold /Courier-BoldOblique /Courier-Oblique /Helvetica /Helvetica-Bold /Helvetica-BoldOblique /Helvetica-Oblique /Symbol /Times-Bold /Times-BoldItalic /Times-Italic /Times-Roman /ZapfDingbats ] /AntiAliasColorImages false /CropColorImages true /ColorImageMinResolution 150 /ColorImageMinResolutionPolicy /OK /DownsampleColorImages true /ColorImageDownsampleType /Bicubic /ColorImageResolution 175 /ColorImageDepth -1 /ColorImageMinDownsampleDepth 1 /ColorImageDownsampleThreshold 1.50286 /EncodeColorImages true /ColorImageFilter /DCTEncode /AutoFilterColorImages false /ColorImageAutoFilterStrategy /JPEG2000 /ColorACSImageDict << /QFactor 0.40 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.40 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 20 >> /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 15 >> /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 150 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 175 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.50286 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages false /GrayImageAutoFilterStrategy /JPEG2000 /GrayACSImageDict << /QFactor 0.40 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.40 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 20 >> /JPEG2000GrayImageDict << /TileWidth 256 /TileHeight 256 /Quality 15 >> /AntiAliasMonoImages true /CropMonoImages true /MonoImageMinResolution 1200 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 175 /MonoImageDepth 4 /MonoImageDownsampleThreshold 1.50286 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict << /K -1 >> /AllowPSXObjects true /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (None) /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False /CreateJDFFile false /Description << /ENU () >> >> setdistillerparams << /HWResolution [600 600] /PageSize [612.000 792.000] >> setpagedevice