| 31. |
- McCarthy, Shane, et al.
(author)
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A reference panel of 64,976 haplotypes for genotype imputation
- 2016
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 48:10, s. 1279-1283
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Journal article (peer-reviewed)abstract
- We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
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| 32. |
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| 33. |
- Charney, Alexander W, et al.
(author)
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Contribution of Rare Copy Number Variants to Bipolar Disorder Risk Is Limited to Schizoaffective Cases.
- 2019
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In: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 86:2, s. 110-119
-
Journal article (peer-reviewed)abstract
- Genetic risk for bipolar disorder (BD) is conferred through many common alleles, while a role for rare copy number variants (CNVs) is less clear. Subtypes of BD including schizoaffective disorder bipolar type (SAB), bipolar I disorder (BD I), and bipolar II disorder (BD II) differ according to the prominence and timing of psychosis, mania, and depression. The genetic factors contributing to the combination of symptoms among these subtypes are poorly understood.Rare large CNVs were analyzed in 6353 BD cases (3833 BD I [2676 with psychosis, 850 without psychosis, and 307 with unknown psychosis history], 1436 BD II, 579 SAB, and 505 BD not otherwise specified) and 8656 controls. CNV burden and a polygenic risk score (PRS) for schizophrenia were used to evaluate the relative contributions of rare and common variants to risk of BD, BD subtypes, and psychosis.CNV burden did not differ between BD and controls when treated as a single diagnostic entity. However, burden in SAB was increased relative to controls (p = .001), BD I (p = .0003), and BD II (p = .0007). Burden and schizophrenia PRSs were increased in SAB compared with BD I with psychosis (CNV p = .0007, PRS p = .004), and BD I without psychosis (CNV p = .0004, PRS p = 3.9 × 10-5). Within BD I, psychosis was associated with increased schizophrenia PRSs (p = .005) but not CNV burden.CNV burden in BD is limited to SAB. Rare and common genetic variants may contribute differently to risk for psychosis and perhaps other classes of psychiatric symptoms.
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| 34. |
- Chen, C. Y., et al.
(author)
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Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records
- 2018
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In: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 8:1, s. 1-8
-
Journal article (peer-reviewed)abstract
- Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363-372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h 2 g) and genetic correlation (r g) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency-"coded-strict", "coded-broad", and "coded-broad based on a single clinical encounter" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h 2 g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h 2 g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h 2 g) was 0.12 (p = 0.004). These h 2 g were lower or similar to the h 2 g observed by the ICCBD + PGCBD (0.23, p = 3.17E-80, total N = 33,181). However, the r g between ICCBD + PGCBD and the EHR-based cases were high for 95-NLP (0.66, p = 3.69 × 10-5), coded-strict (1.00, p = 2.40 × 10-4), and coded-broad (0.74, p = 8.11 × 10-7). The r g between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.
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| 35. |
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| 36. |
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| 37. |
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| 38. |
- Ruderfer, Douglas M., et al.
(author)
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Mosaic copy number variation in schizophrenia
- 2013
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In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 21:9, s. 1007-1011
-
Journal article (peer-reviewed)abstract
- Recent reports suggest that somatic structural changes occur in the human genome, but how these genomic alterations might contribute to disease is unknown. Using samples collected as part of the International Schizophrenia Consortium (schizophrenia, n = 3518; control, n = 4238) recruited across multiple university research centers, we assessed single-nucleotide polymorphism genotyping arrays for evidence of chromosomal anomalies. Data from genotyping arrays on each individual were processed using Birdsuite and analyzed with PLINK. We validated potential chromosomal anomalies using custom nanostring probes and quantitative PCR. We estimate chromosomal alterations in the schizophrenia population to be 0.42%, which is not significantly different from controls (0.26%). We identified and validated a set of four extremely large (>10 Mb) chromosomal anomalies in subjects with schizophrenia, including a chromosome 8 trisomy and deletion of the q arm of chromosome 7. These data demonstrate that chromosomal anomalies are present at low frequency in blood cells of both control and schizophrenia subjects.
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| 39. |
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| 40. |
- Whiffin, N, et al.
(author)
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The effect of LRRK2 loss-of-function variants in humans
- 2020
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In: Nature medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 26:6, s. 869-877
-
Journal article (peer-reviewed)abstract
- Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson’s disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns5–8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9, 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work10, confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.
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