Polygenic Risk Scores Expand to Obesity.

Obesity is one of the most serious health challenges of our time. In this issue of Cell, Khera and co-authors demonstrate the striking ability of genetics, in the form of a polygenic risk score, to identify those individuals at high risk for obesity. This genetic risk expresses itself early as childhood obesity, reinforcing the notion that early prevention is essential to combatting the obesity epidemic.

Unveiling the Role of the Most Impactful Cardiovascular Risk Locus through Haplotype Editing.

The 9p21.3 cardiovascular disease locus is the most influential common genetic risk factor for coronary artery disease (CAD), accounting for ∼10%-15% of disease in non-African populations. The ∼60 kb risk haplotype is human-specific and lacks coding genes, hindering efforts to decipher its function. Here, we produce induced pluripotent stem cells (iPSCs) from risk and non-risk individuals, delete each haplotype using genome editing, and generate vascular smooth muscle cells (VSMCs). Risk VSMCs exhibit globally altered transcriptional networks that intersect with previously identified CAD risk genes and pathways, concomitant with aberrant adhesion, contraction, and proliferation. Unexpectedly, deleting the risk haplotype rescues VSMC stability, while expressing the 9p21.3-associated long non-coding RNA ANRIL induces risk phenotypes in non-risk VSMCs. This study shows that the risk haplotype selectively predisposes VSMCs to adopt a cell state associated with CAD phenotypes, defines new VSMC-based networks of CAD risk genes, and establishes haplotype-edited iPSCs as powerful tools for functionally annotating the human genome.

High-Definition Medicine.

The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution-what we refer to as high-definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging, and behavioral tracking. Our ability to understand and act upon these observations at equally high precision is driven by advances in genome editing, cellular reprogramming, tissue engineering, and information technologies, especially artificial intelligence. In this review, we will examine the core disciplines that enable high-definition medicine and project how these technologies will alter the future of medicine.

Whole-Genome Sequencing of a Healthy Aging Cohort.

Studies of long-lived individuals have revealed few genetic mechanisms for protection against age-associated disease. Therefore, we pursued genome sequencing of a related phenotype-healthy aging-to understand the genetics of disease-free aging without medical intervention. In contrast with studies of exceptional longevity, usually focused on centenarians, healthy aging is not associated with known longevity variants, but is associated with reduced genetic susceptibility to Alzheimer and coronary artery disease. Additionally, healthy aging is not associated with a decreased rate of rare pathogenic variants, potentially indicating the presence of disease-resistance factors. In keeping with this possibility, we identify suggestive common and rare variant genetic associations implying that protection against cognitive decline is a genetic component of healthy aging. These findings, based on a relatively small cohort, require independent replication. Overall, our results suggest healthy aging is an overlapping but distinct phenotype from exceptional longevity that may be enriched with disease-protective genetic factors. VIDEO ABSTRACT.

Reshaping antibody diversity.

Some species mount a robust antibody response despite having limited genome-encoded combinatorial diversity potential. Cows are unusual in having exceptionally long CDR H3 loops and few V regions, but the mechanism for creating diversity is not understood. Deep sequencing reveals that ultralong CDR H3s contain a remarkable complexity of cysteines, suggesting that disulfide-bonded minidomains may arise during repertoire development. Indeed, crystal structures of two cow antibodies reveal that these CDR H3s form a very unusual architecture composed of a ß strand "stalk" that supports a structurally diverse, disulfide-bonded "knob" domain. Diversity arises from somatic hypermutation of an ultralong DH with a severe codon bias toward mutation to cysteine. These unusual antibodies can be elicited to recognize defined antigens through the knob domain. Thus, the bovine immune system produces an antibody repertoire composed of ultralong CDR H3s that fold into a diversity of minidomains generated through combinations of somatically generated disulfides.

Ebola Virus Transmission Initiated by Relapse of Systemic Ebola Virus Disease.

During the 2018-2020 Ebola virus disease (EVD) outbreak in North Kivu province in the Democratic Republic of Congo, EVD was diagnosed in a patient who had received the recombinant vesicular stomatitis virus-based vaccine expressing a ZEBOV glycoprotein (rVSV-ZEBOV) (Merck). His treatment included an Ebola virus (EBOV)-specific monoclonal antibody (mAb114), and he recovered within 14 days. However, 6 months later, he presented again with severe EVD-like illness and EBOV viremia, and he died. We initiated epidemiologic and genomic investigations that showed that the patient had had a relapse of acute EVD that led to a transmission chain resulting in 91 cases across six health zones over 4 months. (Funded by the Bill and Melinda Gates Foundation and others.).

Genome-Wide Analysis of Structural Variants in Parkinson Disease.

OBJECTIVE: Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD. METHODS: We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data. RESULTS: We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2 kb intronic deletion within the gene LRRN4. INTERPRETATION: We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

The personal and clinical utility of polygenic risk scores.

Initial expectations for genome-wide association studies were high, as such studies promised to rapidly transform personalized medicine with individualized disease risk predictions, prevention strategies and treatments. Early findings, however, revealed a more complex genetic architecture than was anticipated for most common diseases - complexity that seemed to limit the immediate utility of these findings. As a result, the practice of utilizing the DNA of an individual to predict disease has been judged to provide little to no useful information. Nevertheless, recent efforts have begun to demonstrate the utility of polygenic risk profiling to identify groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to disease. In this context, we review the evidence supporting the personal and clinical utility of polygenic risk profiling.

Large-scale rare variant burden testing in Parkinson's disease.

Parkinson's disease has a large heritable component and genome-wide association studies have identified over 90 variants with disease-associated common variants, providing deeper insights into the disease biology. However, there have not been large-scale rare variant analyses for Parkinson's disease. To address this gap, we investigated the rare genetic component of Parkinson's disease at minor allele frequencies <1%, using whole genome and whole exome sequencing data from 7184 Parkinson's disease cases, 6701 proxy cases and 51 650 healthy controls from the Accelerating Medicines Partnership Parkinson's disease (AMP-PD) initiative, the National Institutes of Health, the UK Biobank and Genentech. We performed burden tests meta-analyses on small indels and single nucleotide protein-altering variants, prioritized based on their predicted functional impact. Our work identified several genes reaching exome-wide significance. Two of these genes, GBA1 and LRRK2, have variants that have been previously implicated as risk factors for Parkinson's disease, with some variants in LRRK2 resulting in monogenic forms of the disease. We identify potential novel risk associations for variants in B3GNT3, AUNIP, ADH5, TUBA1B, OR1G1, CAPN10 and TREML1 but were unable to replicate the observed associations across independent datasets. Of these, B3GNT3 and TREML1 could provide new evidence for the role of neuroinflammation in Parkinson's disease. To date, this is the largest analysis of rare genetic variants in Parkinson's disease.

Diverse reprogramming codes for neuronal identity.

The transcriptional programs that establish neuronal identity evolved to produce the rich diversity of neuronal cell types that arise sequentially during development. Remarkably, transient expression of certain transcription factors can also endow non-neural cells with neuronal properties. The relationship between reprogramming factors and the transcriptional networks that produce neuronal identity and diversity remains largely unknown. Here, from a screen of 598 pairs of transcription factors, we identify 76 pairs of transcription factors that induce mouse fibroblasts to differentiate into cells with neuronal features. By comparing the transcriptomes of these induced neuronal cells (iN cells) with those of endogenous neurons, we define a 'core' cell-autonomous neuronal signature. The iN cells also exhibit diversity; each transcription factor pair produces iN cells with unique transcriptional patterns that can predict their pharmacological responses. By linking distinct transcription factor input 'codes' to defined transcriptional outputs, this study delineates cell-autonomous features of neuronal identity and diversity and expands the reprogramming toolbox to facilitate engineering of induced neurons with desired patterns of gene expression and related functional properties.

Nidogen-1 could play a role in diabetic kidney disease development in type 2 diabetes: a genome-wide association meta-analysis.

BACKGROUND: Diabetic kidney disease (DKD) affects about 40% of patients with diabetes. It is incurable and usually leads to end-stage renal disease (ESRD). The pathogenesis of DKD is still not fully understood, and the genetics of DKD have not yet been extensively studied. In this study, we investigate the genetic basis of DKD in type 2 diabetes (T2D) to provide more insights into the pathogenesis of the disease. RESULTS: Using the data provided by the UK Biobank (UKBB), we performed a DKD genome-wide association study (GWAS) in 13,123 individuals with T2D as well as two creatinine estimated glomerular filtration rate (eGFR) GWA studies: one in 26,786 individuals with T2D and the other in 339,080 non-diabetic individuals. We also conducted a DKD GWAS meta-analysis combining our results with those published by the surrogate markers for micro- and macro-vascular hard endpoints for Innovative diabetes Tools (SUMMIT) consortium. We confirm two loci previously reported to be associated with chronic kidney disease (CKD) and eGFR in T2D. The UMOD-PDILT locus is associated with DKD (P = 1.17E-09) as well as creatinine eGFR in both people with T2D (P = 1.31E-15) and people without diabetes (P = 3.95E-73). The PRKAG2 locus is associated with creatinine eGFR in people with (P = 2.78E-10) and without (P = 5.65E-72) T2D. Our meta-analysis reveals a novel association between DKD and variant rs72763500 (chr1:236116561) which is a splicing quantitative trait locus (sQTL) for nidogen-1 (NID1) gene. CONCLUSION: Our data confirm two loci previously reported in association with CKD and creatinine eGFR in T2D. It also suggests that NID1, a major component of the renal tubular basement membrane, could play a role in DKD development in T2D. While our NID1 finding remains to be replicated, it is a step toward a more comprehensive understanding of DKD pathogenesis.

Endocannabinoid dysfunction in neurological disease: neuro-ocular DAGLA-related syndrome.

The endocannabinoid system is a highly conserved and ubiquitous signalling pathway with broad-ranging effects. Despite critical pathway functions, gene variants have not previously been conclusively linked to human disease. We identified nine children from eight families with heterozygous, de novo truncating variants in the last exon of DAGLA with a neuro-ocular phenotype characterized by developmental delay, ataxia and complex oculomotor abnormality. All children displayed paroxysms of nystagmus or eye deviation accompanied by compensatory head posture and worsened incoordination most frequently after waking. RNA sequencing showed clear expression of the truncated transcript and no differences were found between mutant and wild-type DAGLA activity. Immunofluorescence staining of patient-derived fibroblasts and HEK cells expressing the mutant protein showed distinct perinuclear aggregation not detected in control samples. This report establishes truncating variants in the last DAGLA exon as the cause of a unique paediatric syndrome. Because enzymatic activity was preserved, the observed mislocalization of the truncated protein may account for the observed phenotype. Potential mechanisms include DAGLA haploinsufficiency at the plasma membrane or dominant negative effect. To our knowledge, this is the first report directly linking an endocannabinoid system component with human genetic disease and sets the stage for potential future therapeutic avenues.

Gain of function of a metalloproteinase associated with multiple myeloma, bicuspid aortic valve, and Von Hippel-Lindau syndrome.

A patient diagnosed with multiple myeloma, bicuspid aortic valve, and Von Hippel-Lindau syndrome underwent whole-exome sequencing seeking a unified genetic cause for these three pathologies. The patient possessed a single-point mutation of arginine to cysteine (R24C) in the N-terminal region(pro-domain) of matrix metalloproteinase 9 (MMP-9). The pro-domain interacts with the catalytic site of this enzyme rendering it inactive. MMP-9 has previously been associated with all three pathologies suffered by the patient. We hypothesized that the observed mutation in the pro-domain would influence the activity of this enzyme. We expressed recombinant versions of MMP-9 and an investigation of their biochemical properties revealed that MMP-9 R24C is a constitutively active zymogen. To our knowledge, this is the first example of a mutation that discloses catalytic activity in the pro-form in any of the 24 human MMPs.

AudioChip: A Deep Phenotyping Approach for Deconstructing and Quantifying Audiological Phenotypes of Self-Reported Speech Perception Difficulties.

OBJECTIVES: About 15% of U.S. adults report speech perception difficulties despite showing normal audiograms. Recent research suggests that genetic factors might influence the phenotypic spectrum of speech perception difficulties. The primary objective of the present study was to describe a conceptual framework of a deep phenotyping method, referred to as AudioChipping, for deconstructing and quantifying complex audiometric phenotypes. DESIGN: In a sample of 70 females 18 to 35 years of age with normal audiograms (from 250 to 8000 Hz), the study measured behavioral hearing thresholds (250 to 16,000 Hz), distortion product otoacoustic emissions (1000 to 16,000 Hz), click-evoked auditory brainstem responses (ABR), complex ABR (cABR), QuickSIN, dichotic digit test score, loudness discomfort level, and noise exposure background. The speech perception difficulties were evaluated using the Speech, Spatial, and Quality of Hearing Scale-12-item version (SSQ). A multiple linear regression model was used to determine the relationship between SSQ scores and audiometric measures. Participants were categorized into three groups (i.e., high, mid, and low) using the SSQ scores before performing the clustering analysis. Audiometric measures were normalized and standardized before performing unsupervised k-means clustering to generate AudioChip. RESULTS: The results showed that SSQ and noise exposure background exhibited a significant negative correlation. ABR wave I amplitude, cABR offset latency, cABR response morphology, and loudness discomfort level were significant predictors for SSQ scores. These predictors explained about 18% of the variance in the SSQ score. The k-means clustering was used to split the participants into three major groups; one of these clusters revealed 53% of participants with low SSQ. CONCLUSIONS: Our study highlighted the relationship between SSQ and auditory coding precision in the auditory brainstem in normal-hearing young females. AudioChip was useful in delineating and quantifying internal homogeneity and heterogeneity in audiometric measures among individuals with a range of SSQ scores. AudioChip could help identify the genotype-phenotype relationship, document longitudinal changes in auditory phenotypes, and pair individuals in case-control groups for the genetic association analysis.

Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.

BACKGROUND: Next Generation Sequencing (NGS) is the fundament of various studies, providing insights into questions from biology and medicine. Nevertheless, integrating data from different experimental backgrounds can introduce strong biases. In order to methodically investigate the magnitude of systematic errors in single nucleotide variant calls, we performed a cross-sectional observational study on a genomic cohort of 99 subjects each sequenced via (i) Illumina HiSeq X, (ii) Illumina HiSeq, and (iii) Complete Genomics and processed with the respective bioinformatic pipeline. We also repeated variant calling for the Illumina cohorts with GATK, which allowed us to investigate the effect of the bioinformatics analysis strategy separately from the sequencing platform's impact. RESULTS: The number of detected variants/variant classes per individual was highly dependent on the experimental setup. We observed a statistically significant overrepresentation of variants uniquely called by a single setup, indicating potential systematic biases. Insertion/deletion polymorphisms (indels) were associated with decreased concordance compared to single nucleotide polymorphisms (SNPs). The discrepancies in indel absolute numbers were particularly prominent in introns, Alu elements, simple repeats, and regions with medium GC content. Notably, reprocessing sequencing data following the best practice recommendations of GATK considerably improved concordance between the respective setups. CONCLUSION: We provide empirical evidence of systematic heterogeneity in variant calls between alternative experimental and data analysis setups. Furthermore, our results demonstrate the benefit of reprocessing genomic data with harmonized pipelines when integrating data from different studies.

Drilling for Insight: Forecasting Phenotype from Genotype.

The manifestation of disease can vary substantially from person to person. Yet, much of the emphasis of genomics in individualized medicine has been on linking genetic variants to broad disease categories. A new approach takes a first step towards predicting detailed phenotypic information from disease-causative variants.

Genomic medicine implementation protocols in the PhenX Toolkit: tools for standardized data collection.

PURPOSE: The PhenX Toolkit ( www.phenxtoolkit.org ), an online catalog of recommended measurement protocols, facilitates cross-study analyses for research with human participants. The PhenX Steering Committee recommended genomic medicine implementation as a new research domain, with the following scope: genomic knowledge and education (both patients and providers); implementation science; changes in management and treatment; return of results; patient outcomes; and ethical, legal, and social issues (ELSI) associated with genomic research. METHODS: A seven-member expert Working Group convened in October 2019 to identify well-established measurement protocols for a new genomic medicine implementation domain and used the established PhenX consensus process to select measurement protocols for inclusion in the PhenX Toolkit. RESULTS: The Working Group recommended 15 measurement protocols for inclusion in the PhenX Toolkit, with priority given to those with empirical evidence supporting validity. Consortia funded by the National Institutes of Health, and particularly the National Human Genome Research Institute, proved critical in identifying protocols with established utility in this research domain, and identified protocols that were developed through a rigorous process for scope elements that lacked formally validated protocols. CONCLUSION: Use of these protocols, which were released in September 2020, can facilitate standard data collection for genomic medicine implementation research.

Monogenic and Polygenic Models of Coronary Artery Disease.

PURPOSE OF THE REVIEW: Coronary artery disease (CAD) is a common disease globally attributable to the interplay of complex genetic and lifestyle factors. Here, we review how genomic sequencing advances have broadened the fundamental understanding of the monogenic and polygenic contributions to CAD and how these insights can be utilized, in part by creating polygenic risk estimates, for improved disease risk stratification at the individual patient level. RECENT FINDINGS: Initial studies linking premature CAD with rare familial cases of elevated blood lipids highlighted high-risk monogenic contributions, predominantly presenting as familial hypercholesterolemia (FH). More commonly CAD genetic risk is a function of multiple, higher frequency variants each imparting lower magnitude of risk, which can be combined to form polygenic risk scores (PRS) conveying significant risk to individuals at the extremes. However, gaps remain in clinical validation of PRSs, most notably in non-European populations. With improved and more broadly utilized genomic sequencing technologies, the genetic underpinnings of coronary artery disease are being unraveled. As a result, polygenic risk estimation is poised to become a widely used and powerful tool in the clinical setting. While the use of PRSs to augment current clinical risk stratification for optimization of cardiovascular disease risk by lifestyle change or therapeutic targeting is promising, we await adequately powered, prospective studies, demonstrating the clinical utility of polygenic risk estimation in practice.

Mutations of the mitochondrial carrier translocase channel subunit TIM22 cause early-onset mitochondrial myopathy.

Protein import into mitochondria is facilitated by translocases within the outer and the inner mitochondrial membranes that are dedicated to a highly specific subset of client proteins. The mitochondrial carrier translocase (TIM22 complex) inserts multispanning proteins, such as mitochondrial metabolite carriers and translocase subunits (TIM23, TIM17A/B and TIM22), into the inner mitochondrial membrane. Both types of substrates are essential for mitochondrial metabolic function and biogenesis. Here, we report on a subject, diagnosed at 1.5 years, with a neuromuscular presentation, comprising hypotonia, gastroesophageal reflux disease and persistently elevated serum and Cerebrospinal fluid lactate (CSF). Patient fibroblasts displayed reduced oxidative capacity and altered mitochondrial morphology. Using trans-mitochondrial cybrid cell lines, we excluded a candidate variant in mitochondrial DNA as causative of these effects. Whole-exome sequencing identified compound heterozygous variants in the TIM22 gene (NM_013337), resulting in premature truncation in one allele (p.Tyr25Ter) and a point mutation in a conserved residue (p.Val33Leu), within the intermembrane space region, of the TIM22 protein in the second allele. Although mRNA transcripts of TIM22 were elevated, biochemical analyses revealed lower levels of TIM22 protein and an even greater deficiency of TIM22 complex formation. In agreement with a defect in carrier translocase function, carrier protein amounts in the inner membrane were found to be reduced. This is the first report of pathogenic variants in the TIM22 pore-forming subunit of the carrier translocase affecting the biogenesis of inner mitochondrial membrane proteins critical for metabolite exchange.

Novel exomic rare variants associated with venous thrombosis.

Exomic rare variant polymorphisms (c. 300 000) were analysed in the Scripps Venous Thrombosis (VTE) registry (subjects aged <55 years). Besides coagulation factor V (F5) single nucleotide polymorphisms (SNPs), family with sequence similarity 134, member B (FAM134B; rs78314670, Arg127Cys) and myosin heavy chain 8 (MYH8; rs111567318, Glu1838Ala) SNPs were associated with recurrent VTE (n = 34 cases) (false discovery rate-adjusted P < 0·05). FAM134B (rs78314670) was associated with low plasma levels of anticoagulant glucosylceramide. Analysis of 50 chr17p13.1 MYH rare SNPs (clustered skeletal myosin heavy chain genes) using collapsing methods was associated with recurrent VTE (P = 2·70 ×10-16 ). When intravenously injected, skeletal muscle myosin was pro-coagulant in a haemophilia mouse tail bleeding model. Thus, FAM134B and MYH genetic variants are plausibly linked to VTE risk.