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In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments., (Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

In this exciting era of "next-gen cytogenetics," integrating genomic sequencing into the prenatal diagnostic setting is possible within an actionable time frame and can provide precise delineation of balanced chromosomal rearrangements at the nucleotide level. Given the increased risk of congenital abnormalities in newborns with de novo balanced chromosomal rearrangements, comprehensive interpretation of breakpoints could substantially improve prediction of phenotypic outcomes and support perinatal medical care. Herein, we present and evaluate sequencing results of balanced chromosomal rearrangements in ten prenatal subjects with respect to the location of regulatory chromatin domains (topologically associated domains [TADs]). The genomic material from all subjects was interpreted to be "normal" by microarray analyses, and their rearrangements would not have been detected by cell-free DNA (cfDNA) screening. The findings of our systematic approach correlate with phenotypes of both pregnancies with untoward outcomes (5/10) and with healthy newborns (3/10). Two pregnancies, one with a chromosomal aberration predicted to be of unknown clinical significance and another one predicted to be likely benign, were terminated prior to phenotype-genotype correlation (2/10). We demonstrate that the clinical interpretation of structural rearrangements should not be limited to interruption, deletion, or duplication of specific genes and should also incorporate regulatory domains of the human genome with critical ramifications for the control of gene expression. As detailed in this study, our molecular approach to both detecting and interpreting the breakpoints of structural rearrangements yields unparalleled information in comparison to other commonly used first-tier diagnostic methods, such as non-invasive cfDNA screening and microarray analysis, to provide improved genetic counseling for phenotypic outcome in the prenatal setting., (Copyright © 2016 American Society of Human Genetics. All rights reserved.)

ATPase family AAA-domain containing protein 3A (ATAD3A) is a nuclear-encoded mitochondrial membrane protein implicated in mitochondrial dynamics, nucleoid organization, protein translation, cell growth, and cholesterol metabolism. We identified a recurrent de novo ATAD3A c.1582C>T (p.Arg528Trp) variant by whole-exome sequencing (WES) in five unrelated individuals with a core phenotype of global developmental delay, hypotonia, optic atrophy, axonal neuropathy, and hypertrophic cardiomyopathy. We also describe two families with biallelic variants in ATAD3A, including a homozygous variant in two siblings, and biallelic ATAD3A deletions mediated by nonallelic homologous recombination (NAHR) between ATAD3A and gene family members ATAD3B and ATAD3C. Tissue-specific overexpression of bor R534W , the Drosophila mutation homologous to the human c.1582C>T (p.Arg528Trp) variant, resulted in a dramatic decrease in mitochondrial content, aberrant mitochondrial morphology, and increased autophagy. Homozygous null bor larvae showed a significant decrease of mitochondria, while overexpression of bor WT resulted in larger, elongated mitochondria. Finally, fibroblasts of an affected individual exhibited increased mitophagy. We conclude that the p.Arg528Trp variant functions through a dominant-negative mechanism that results in small mitochondria that trigger mitophagy, resulting in a reduction in mitochondrial content. ATAD3A variation represents an additional link between mitochondrial dynamics and recognizable neurological syndromes, as seen with MFN2, OPA1, DNM1L, and STAT2 mutations., (Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis., (Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated., (Copyright © 2016 American Society of Human Genetics. All rights reserved.)

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors., (Published by Elsevier Inc.)

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci., (Copyright © 2016 American Society of Human Genetics. All rights reserved.)

Huntington disease (HD) is caused by an expanded HTT CAG repeat that leads in a length-dependent, completely dominant manner to onset of a characteristic movement disorder. HD also displays early mortality, so we tested whether the expanded CAG repeat exerts a dominant influence on age at death and on the duration of clinical disease. We found that, as with clinical onset, HD age at death is determined by expanded CAG-repeat length and has no contribution from the normal CAG allele. Surprisingly, disease duration is independent of the mutation's length. It is also unaffected by a strong genetic modifier of HD motor onset. These findings suggest two parsimonious alternatives. (1) HD pathogenesis is driven by mutant huntingtin, but before or near motor onset, sufficient CAG-driven damage occurs to permit CAG-independent processes and then lead to eventual death. In this scenario, some pathological changes and their clinical correlates could still worsen in a CAG-driven manner after disease onset, but these CAG-related progressive changes do not themselves determine duration. Alternatively, (2) HD pathogenesis is driven by mutant huntingtin acting in a CAG-dependent manner with different time courses in multiple cell types, and the cellular targets that lead to motor onset and death are different and independent. In this scenario, processes driven by HTT CAG length lead directly to death but not via the striatal pathology associated with motor manifestations. Each scenario has important ramifications for the design and testing of potential therapeutics, especially those aimed at preventing or delaying characteristic motor manifestations., (Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Huntington disease (HD) reflects the dominant consequences of a CAG-repeat expansion in HTT. Analysis of common SNP-based haplotypes has revealed that most European HD subjects have distinguishable HTT haplotypes on their normal and disease chromosomes and that ∼50% of the latter share the same major HD haplotype. We reasoned that sequence-level investigation of this founder haplotype could provide significant insights into the history of HD and valuable information for gene-targeting approaches. Consequently, we performed whole-genome sequencing of HD and control subjects from four independent families in whom the major European HD haplotype segregates with the disease. Analysis of the full-sequence-based HTT haplotype indicated that these four families share a common ancestor sufficiently distant to have permitted the accumulation of family-specific variants. Confirmation of new CAG-expansion mutations on this haplotype suggests that unlike most founders of human disease, the common ancestor of HD-affected families with the major haplotype most likely did not have HD. Further, availability of the full sequence data validated the use of SNP imputation to predict the optimal variants for capturing heterozygosity in personalized allele-specific gene-silencing approaches. As few as ten SNPs are capable of revealing heterozygosity in more than 97% of European HD subjects. Extension of allele-specific silencing strategies to the few remaining homozygous individuals is likely to be achievable through additional known SNPs and discovery of private variants by complete sequencing of HTT. These data suggest that the current development of gene-based targeting for HD could be extended to personalized allele-specific approaches in essentially all HD individuals of European ancestry., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Copy-number variants (CNVs) have been the predominant focus of genetic studies of structural variation, and chromosomal microarray (CMA) for genome-wide CNV detection is the recommended first-tier genetic diagnostic screen in neurodevelopmental disorders. We compared CNVs observed by CMA to the structural variation detected by whole-genome large-insert sequencing in 259 individuals diagnosed with autism spectrum disorder (ASD) from the Simons Simplex Collection. These analyses revealed a diverse landscape of complex duplications in the human genome. One remarkably common class of complex rearrangement, which we term dupINVdup, involves two closely located duplications ("paired duplications") that flank the breakpoints of an inversion. This complex variant class is cryptic to CMA, but we observed it in 8.1% of all subjects. We also detected other paired-duplication signatures and duplication-mediated complex rearrangements in 15.8% of all ASD subjects. Breakpoint analysis showed that the predominant mechanism of formation of these complex duplication-associated variants was microhomology-mediated repair. On the basis of the striking prevalence of dupINVdups in this cohort, we explored the landscape of all inversion variation among the 235 highest-quality libraries and found abundant complexity among these variants: only 39.3% of inversions were canonical, or simple, inversions without additional rearrangement. Collectively, these findings indicate that dupINVdups, as well as other complex duplication-associated rearrangements, represent relatively common sources of genomic variation that is cryptic to population-based microarray and low-depth whole-genome sequencing. They also suggest that paired-duplication signatures detected by CMA warrant further scrutiny in genetic diagnostic testing given that they might mark complex rearrangements of potential clinical relevance., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

The 16p11.2 600 kb copy-number variants (CNVs) are associated with mirror phenotypes on BMI, head circumference, and brain volume and represent frequent genetic lesions in autism spectrum disorders (ASDs) and schizophrenia. Here we interrogated the transcriptome of individuals carrying reciprocal 16p11.2 CNVs. Transcript perturbations correlated with clinical endophenotypes and were enriched for genes associated with ASDs, abnormalities of head size, and ciliopathies. Ciliary gene expression was also perturbed in orthologous mouse models, raising the possibility that ciliary dysfunction contributes to 16p11.2 pathologies. In support of this hypothesis, we found structural ciliary defects in the CA1 hippocampal region of 16p11.2 duplication mice. Moreover, by using an established zebrafish model, we show genetic interaction between KCTD13, a key driver of the mirrored neuroanatomical phenotypes of the 16p11.2 CNV, and ciliopathy-associated genes. Overexpression of BBS7 rescues head size and neuroanatomical defects of kctd13 morphants, whereas suppression or overexpression of CEP290 rescues phenotypes induced by KCTD13 under- or overexpression, respectively. Our data suggest that dysregulation of ciliopathy genes contributes to the clinical phenotypes of these CNVs., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Structural variation (SV) is a significant component of the genetic etiology of both neurodevelopmental and psychiatric disorders; however, routine guidelines for clinical genetic screening have been established only in the former category. Genome-wide chromosomal microarray (CMA) can detect genomic imbalances such as copy-number variants (CNVs), but balanced chromosomal abnormalities (BCAs) still require karyotyping for clinical detection. Moreover, submicroscopic BCAs and subarray threshold CNVs are intractable, or cryptic, to both CMA and karyotyping. Here, we performed whole-genome sequencing using large-insert jumping libraries to delineate both cytogenetically visible and cryptic SVs in a single test among 30 clinically referred youth representing a range of severe neuropsychiatric conditions. We detected 96 SVs per person on average that passed filtering criteria above our highest-confidence resolution (6,305 bp) and an additional 111 SVs per genome below this resolution. These SVs rearranged 3.8 Mb of genomic sequence and resulted in 42 putative loss-of-function (LoF) or gain-of-function mutations per person. We estimate that 80% of the LoF variants were cryptic to clinical CMA. We found myriad complex and cryptic rearrangements, including a "paired" duplication (360 kb, 169 kb) that flanks a 5.25 Mb inversion that appears in 7 additional cases from clinical CNV data among 47,562 individuals. Following convergent genomic profiling of these independent clinical CNV data, we interpreted three SVs to be of potential clinical significance. These data indicate that sequence-based delineation of the full SV mutational spectrum warrants exploration in youth referred for neuropsychiatric evaluation and clinical diagnostic SV screening more broadly., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Reciprocal copy-number variation (CNV) of a 593 kb region of 16p11.2 is a common genetic cause of autism spectrum disorder (ASD), yet it is not completely penetrant and can manifest in a wide array of phenotypes. To explore its molecular consequences, we performed RNA sequencing of cerebral cortex from mouse models with CNV of the syntenic 7qF3 region and lymphoblast lines from 34 members of 7 multiplex ASD-affected families harboring the 16p11.2 CNV. Expression of all genes in the CNV region correlated well with their DNA copy number, with no evidence of dosage compensation. We observed effects on gene expression outside the CNV region, including apparent positional effects in cis and in trans at genomic segments with evidence of physical interaction in Hi-C chromosome conformation data. One of the most significant positional effects was telomeric to the 16p11.2 CNV and includes the previously described "distal" 16p11.2 microdeletion. Overall, 16p11.2 CNV was associated with altered expression of genes and networks that converge on multiple hypotheses of ASD pathogenesis, including synaptic function (e.g., NRXN1, NRXN3), chromatin modification (e.g., CHD8, EHMT1, MECP2), transcriptional regulation (e.g., TCF4, SATB2), and intellectual disability (e.g., FMR1, CEP290). However, there were differences between tissues and species, with the strongest effects being consistently within the CNV region itself. Our analyses suggest that through a combination of indirect regulatory effects and direct effects on nuclear architecture, alteration of 16p11.2 genes disrupts expression networks that involve other genes and pathways known to contribute to ASD, suggesting an overlap in mechanisms of pathogenesis., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

With recent rapid advances in genomic technologies, precise delineation of structural chromosome rearrangements at the nucleotide level is becoming increasingly feasible. In this era of "next-generation cytogenetics" (i.e., an integration of traditional cytogenetic techniques and next-generation sequencing), a consensus nomenclature is essential for accurate communication and data sharing. Currently, nomenclature for describing the sequencing data of these aberrations is lacking. Herein, we present a system called Next-Gen Cytogenetic Nomenclature, which is concordant with the International System for Human Cytogenetic Nomenclature (2013). This system starts with the alignment of rearrangement sequences by BLAT or BLAST (alignment tools) and arrives at a concise and detailed description of chromosomal changes. To facilitate usage and implementation of this nomenclature, we are developing a program designated BLA(S)T Output Sequence Tool of Nomenclature (BOSToN), a demonstrative version of which is accessible online. A standardized characterization of structural chromosomal rearrangements is essential both for research analyses and for application in the clinical setting., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Intracerebral hemorrhage (ICH) is the stroke subtype with the worst prognosis and has no established acute treatment. ICH is classified as lobar or nonlobar based on the location of ruptured blood vessels within the brain. These different locations also signal different underlying vascular pathologies. Heritability estimates indicate a substantial genetic contribution to risk of ICH in both locations. We report a genome-wide association study of this condition that meta-analyzed data from six studies that enrolled individuals of European ancestry. Case subjects were ascertained by neurologists blinded to genotype data and classified as lobar or nonlobar based on brain computed tomography. ICH-free control subjects were sampled from ambulatory clinics or random digit dialing. Replication of signals identified in the discovery cohort with p < 1 × 10(-6) was pursued in an independent multiethnic sample utilizing both direct and genome-wide genotyping. The discovery phase included a case cohort of 1,545 individuals (664 lobar and 881 nonlobar cases) and a control cohort of 1,481 individuals and identified two susceptibility loci: for lobar ICH, chromosomal region 12q21.1 (rs11179580, odds ratio [OR] = 1.56, p = 7.0 × 10(-8)); and for nonlobar ICH, chromosomal region 1q22 (rs2984613, OR = 1.44, p = 1.6 × 10(-8)). The replication included a case cohort of 1,681 individuals (484 lobar and 1,194 nonlobar cases) and a control cohort of 2,261 individuals and corroborated the association for 1q22 (p = 6.5 × 10(-4); meta-analysis p = 2.2 × 10(-10)) but not for 12q21.1 (p = 0.55; meta-analysis p = 2.6 × 10(-5)). These results demonstrate biological heterogeneity across ICH subtypes and highlight the importance of ascertaining ICH cases accordingly., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Low-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Large intergenic noncoding (linc) RNAs represent a newly described class of ribonucleic acid whose importance in human disease remains undefined. We identified a severely developmentally delayed 16-year-old female with karyotype 46,XX,t(2;11)(p25.1;p15.1)dn in the absence of clinically significant copy number variants (CNVs). DNA capture followed by next-generation sequencing of the translocation breakpoints revealed disruption of a single noncoding gene on chromosome 2, LINC00299, whose RNA product is expressed in all tissues measured, but most abundantly in brain. Among a series of additional, unrelated subjects referred for clinical diagnostic testing who showed CNV affecting this locus, we identified four with exon-crossing deletions in association with neurodevelopmental abnormalities. No disruption of the LINC00299 coding sequence was seen in almost 14,000 control subjects. Together, these subjects with disruption of LINC00299 implicate this particular noncoding RNA in brain development and raise the possibility that, as a class, abnormalities of lincRNAs may play a significant role in human developmental disorders., (Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Persons with neurodevelopmental disorders or autism spectrum disorder (ASD) often harbor chromosomal microdeletions, yet the individual genetic contributors within these regions have not been systematically evaluated. We established a consortium of clinical diagnostic and research laboratories to accumulate a large cohort with genetic alterations of chromosomal region 2q23.1 and acquired 65 subjects with microdeletion or translocation. We sequenced translocation breakpoints; aligned microdeletions to determine the critical region; assessed effects on mRNA expression; and examined medical records, photos, and clinical evaluations. We identified a single gene, methyl-CpG-binding domain 5 (MBD5), as the only locus that defined the critical region. Partial or complete deletion of MBD5 was associated with haploinsufficiency of mRNA expression, intellectual disability, epilepsy, and autistic features. Fourteen alterations, including partial deletions of noncoding regions not typically captured or considered pathogenic by current diagnostic screening, disrupted MBD5 alone. Expression profiles and clinical characteristics were largely indistinguishable between MBD5-specific alteration and deletion of the entire 2q23.1 interval. No copy-number alterations of MBD5 were observed in 7878 controls, suggesting MBD5 alterations are highly penetrant. We surveyed MBD5 coding variations among 747 ASD subjects compared to 2043 non-ASD subjects analyzed by whole-exome sequencing and detected an association with a highly conserved methyl-CpG-binding domain missense variant, p.79Gly>Glu (c.236G>A) (p = 0.012). These results suggest that genetic alterations of MBD5 cause features of 2q23.1 microdeletion syndrome and that this epigenetic regulator significantly contributes to ASD risk, warranting further consideration in research and clinical diagnostic screening and highlighting the importance of chromatin remodeling in the etiology of these complex disorders., (Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice., (Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Although inherited mitochondrial genetic variation can cause human disease, no validated methods exist for control of confounding due to mitochondrial population stratification (PS). We sought to identify a reliable method for PS assessment in mitochondrial medical genetics. We analyzed mitochondrial SNP data from 1513 European American individuals concomitantly genotyped with the use of a previously validated panel of 144 mitochondrial markers as well as the Affymetrix 6.0 (n = 432), Illumina 610-Quad (n = 458), or Illumina 660 (n = 623) platforms. Additional analyses were performed in 938 participants in the Human Genome Diversity Panel (HGDP) (Illumina 650). We compared the following methods for controlling for PS: haplogroup-stratified analyses, mitochondrial principal-component analysis (PCA), and combined autosomal-mitochondrial PCA. We computed mitochondrial genomic inflation factors (mtGIFs) and test statistics for simulated case-control and continuous phenotypes (10,000 simulations each) with varying degrees of correlation with mitochondrial ancestry. Results were then compared across adjustment methods. We also calculated power for discovery of true associations under each method, using a simulation approach. Mitochondrial PCA recapitulated haplogroup information, but haplogroup-stratified analyses were inferior to mitochondrial PCA in controlling for PS. Correlation between nuclear and mitochondrial principal components (PCs) was very limited. Adjustment for nuclear PCs had no effect on mitochondrial analysis of simulated phenotypes. Mitochondrial PCA performed with the use of data from commercially available genome-wide arrays correlated strongly with PCA performed with the use of an exhaustive mitochondrial marker panel. Finally, we demonstrate, through simulation, no loss in power for detection of true associations with the use of mitochondrial PCA., (Copyright 2010 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.