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McKay, J.

Publications and source records attributed to McKay, J..

5 recordsLinked to original sources

Drought adaptation in nature by extensive genetic loss-of-function

Visions of a second green revolution empowered by emerging technologies have called for interdisciplinary syntheses to scale up the discovery of functionally definitive gene variants responsible for climate adaptation in plants. We integrated novel approaches using whole genome sequences and satellite remote sensing to identify natural knockout alleles associated with drought histories in wild Arabidopsis thaliana. Genes identified exhibit signatures of parallel molecular evolution, selection for loss-of-function alleles, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses 7 times more often than expected by chance. Artificial knockout lines then confirmed predicted phenotypes experimentally. These findings further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature and inspire new opportunities for engineering climate resilience in crops.\n\nOne sentence summaryWhole genome sequences and satellite-detected droughts point to gene knockouts as valuable genetic fuel for climate adaptation.

evolutionary biology

Association between Parkinson’s Disease subtypes and tests of physical function: the 360-degree turn test is most predictive

BACKGROUND AND PURPOSEPeople with Parkinsons disease (PD) present phenotypes that can be characterized as tremor-dominant (TD) or postural instability / gait difficulty (PIGD) subtypes. Differentiation of subtypes allows clinicians to predict the disease course and adjust treatment accordingly. We examined whether brief mobility and balance measures can discriminate PIGD from TD phenotypes.\n\nMETHODSWe performed a cross-sectional study with individuals with PD (N=104). Blinded raters assessed participants with the UPDRS or MDS-UPDRS, and potential predictor variables: 360-degree turn test, one-leg stance, backward perturbation test and tandem walk. Participant were classified as PIGD or TD based on the Unified Parkinsons Disease Rating Scale or the Movement Disorder Society revision (UPDRS or MDS-UPDRS) assessment results. Differences in study variables between subtype groups were assessed with univariate analyses. Receiver operating characteristic (ROC) curve analyses were performed to investigate the ability of candidate predictor variables to differentiate PD subtypes.\n\nRESULTSMean age and disease duration were 68{+/-}9 and 7{+/-}5 years, respectively, and Hoehn & Yahr Stages I-IV median (1st,3rd quartile) = II (II, III). No differences between subtypes were observed for tandem walk or reactive postural control. PIGD participants performed worse on number of steps (p<0.001) and time to complete (p=0.003) the 360-degree turn test and one-leg stance (p=0.006). ROC curves showed only the 360-degree turn test could discriminate PIGD from TD with high sensitivity.\n\nCONCLUSIONSThe 360-degree turn test requires minimal time to administer and may be useful in mild-moderate PD for distinguishing PIGD from TD subtypes.

neuroscience

Experimental analysis of exome-scale mutational signature of glycidamide, the reactive metabolite of acrylamide

Acrylamide, a probable human carcinogen, is ubiquitously present in the human environment, with sources including heated starchy foods, coffee and cigarette smoke. Humans are also exposed to acrylamide occupationally. Acrylamide is genotoxic, inducing gene mutations and chromosomal aberrations in various experimental settings. Covalent haemoglobin adducts were reported in acrylamide-exposed humans and DNA adducts in experimental systems. The carcinogenicity of acrylamide has been attributed to the effects of glycidamide, its reactive and mutagenic metabolite capable of inducing rodent tumors at various anatomical sites. In order to characterize the pre-mutagenic DNA lesions and global mutation spectra induced by acrylamide and glycidamide, we combined DNA-adduct and whole-exome sequencing analyses in an established exposure-clonal immortalization system based on mouse embryonic fibroblasts. Sequencing and computational analysis revealed a unique mutational signature of glycidamide, characterized by predominant T:A>A:T transversions, followed by T:A>C:G and C:G>A:T mutations exhibiting specific trinucleotide contexts and significant transcription strand bias. Computational interrogation of human cancer genome sequencing data indicated that a combination of the glycidamide signature and an experimental benzo[a]pyrene signature are nearly equivalent to the COSMIC tobacco-smoking related signature 4 in lung adenocarcinomas and squamous cell carcinomas. We found a more variable relationship between the glycidamide- and benzo[a]pyrene-signatures and COSMIC signature 4 in liver cancer, indicating more complex exposures in the liver. Our study demonstrates that the controlled experimental characterization of specific genetic damage associated with glycidamide exposure facilitates identifying corresponding patterns in cancer genome data, thereby underscoring how mutation signature laboratory experimentation contributes to the elucidation of cancer causation.\n\nA 40-word summaryInnovative experimental approaches identify a novel mutational signature of glycidamide, a metabolite of the probable human carcinogen acrylamide. The results may elucidate the cancer risks associated with exposure to acrylamide, commonly found in tobacco smoke, thermally processed foods and beverages.

genomics

A Cross-Sectional Study of Set Shifting Impairments and Falling in Individuals with and without Parkinson’s Disease

INTRODUCTION. Individuals with Parkinsons disease (PD) are at increased risk for falls, and exhibit deficits in executive function, including Set Shifting, which can be measured as the difference between parts B and A of the Trailmaking Test. METHODS. We conducted a cross-sectional study using baseline data of PD patients with and without freezing of gait (FOG) (n=69) and community-dwelling neurologically-normal older adults (NON-PD) (n=84) who had volunteered to participate in clinical rehabilitation research. Multivariate logistic regression analyses were performed to determine associations between Set Shifting, PD, and faller status, as determined by [&ge;]1 self-reported falls in the previous 6 months, after adjusting for demographic and cognitive factors and clinical disease characteristics. RESULTS. Impaired Set Shifting was associated with previous falls after controlling for age, sex, overall cognitive function, PD, FOG, and PD disease duration (OR=1.29 [1.03-1.60]; P=0.02). In models controlling for age, sex, and overall cognitive function, PD was associated with increased fall prevalence among the study sample (OR=4.15 [95% CI 1.65-10.44], P<0.01) and FOG was associated with increased fall prevalence among the PD sample (OR=3.63 [1.22-10.80], P=0.02). Although the strongest associations between Set Shifting and falling were observed among PD without FOG (OR=2.11) compared to HOA (OR=1.14) and PD with FOG (OR=1.46) in a multivariate model that allowed for interaction between set shifting and PD status, there was insufficient evidence to reject the null hypothesis of no interaction. CONCLUSIONS. Set Shifting is associated with previous falls in non-demented older adults with and without PD.\n\nHighlightsO_LIIndividuals with PD are at increased risk for falls, although causes are unclear.\nC_LIO_LIImpaired Set Shifting was associated with falls in older adults with and without PD.\nC_LIO_LIAssociations were strongest among those with PD but without freezing of gait.\nC_LI

neuroscience

Novel Pedigree Analysis Implicates DNA Repair And Chromatin Remodeling In Multiple Myeloma Risk

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance - a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691*, p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly, p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.\n\nAUTHOR SUMMARYAlthough family-based studies demonstrate inherited variants play a role in many common and complex diseases, finding the genes responsible remains a challenge. High-risk pedigrees, or families with more disease than expected by chance, have been helpful in the discovery of variants responsible for less complex diseases, but have not reached their potential in complex diseases. Here, we describe a method to utilize high-risk pedigrees to discover risk-genes in complex diseases. Our method is appropriate for complex diseases because it allows for genetic-heterogeneity, or multiple causes of disease, within a pedigree. This method allows us to identify shared segments that likely harbor disease-causing variants in a family. We apply our method in Multiple Myeloma, a heritable and complex cancer of plasma cells. We identified two genes USP45 and ARID1A that fall within shared segments with compelling statistical evidence. Exome sequencing of these genes revealed likely-damaging variants inherited in Myeloma high-risk families, suggesting these genes likely play a role in development of Myeloma. Our Myeloma findings demonstrate our high-risk pedigree method can identify genetic regions of interest in large high-risk pedigrees that are also relevant to smaller nuclear families and overall disease risk. In sum, we offer a strategy, applicable across phenotypes, to revitalize high-risk pedigrees in the discovery of the genetic basis of common and complex disease.

genetics