Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds

We investigate associations between normal-appearing white matter (NAWM) microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 Birth cohort) underwent PET-MRI around age 70. Mean standardized NAWM integrity metrics (fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI) and orientation dispersion index (ODI)) were derived from diffusion MRI. Linear regression was used to test associations between NAWM metrics and (1) concurrent measures, including whole brain volume, white matter hyperintensity volume (WMHV), PET amyloid and cognition; (2) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socioeconomic position, and genetic risk for Alzheimer’s Disease (APOE-ε4); (3) systolic and diastolic blood pressure and cardiovascular health (FHS-CVS) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). 362 participants met inclusion criteria (mean age 70 years, 49% female). Higher WMHV was associated with lower FA (b=-0.09 [95%CI:-0.11, -0.06] p<0.01), NDI (b=-0.17 [-0.22, -0.12] p<0.01), and higher MD (b=0.14 [-0.10, -0.17] p<0.01); amyloid (in men) was associated with lower FA (b=-0.04 [-0.08, -0.01] p=0.03) and higher MD (b=0.06 [0.01,0.11] p=0.02). FHS-CVS in later-life (age 69) was associated with NAWM [lower FA (b=-0.06 [-0.09, -0.02] p<0.01), NDI (b=-0.10 [-0.17, -0.03] p<0.01), and higher MD (b=0.09 [0.04,0.14] p<0.01). Significant sex interactions (p<0.05) emerged for midlife cardiovascular health (age 53) and NAWM at 70: marginal effect plots demonstrated, in women only, NAWM was associated with higher midlife FHS-CVS (lower FA and NDI), midlife systolic (lower FA, NDI, and higher MD), and diastolic (lower FA and NDI) blood pressure, and greater blood pressure change between 43 and 53 years (lower FA and NDI), independently of WMHV. In summary, poorer NAWM microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how NAWM can provide additional information to overt white matter disease. Our findings further show that greater midlife cardiovascular risk and higher blood pressure were associated with poorer NAWM microstructural integrity in females only, suggesting that women’s brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Fil: Dincer, Aylin. Washington University in St. Louis; Estados UnidosFil: Gordon, Brian A.. Washington University in St. Louis; Estados UnidosFil: Hari-Raj, Amrita. Ohio State University; Estados UnidosFil: Keefe, Sarah J.. Washington University in St. Louis; Estados UnidosFil: Flores, Shaney. Washington University in St. Louis; Estados UnidosFil: McKay, Nicole S.. Washington University in St. Louis; Estados UnidosFil: Paulick, Angela M.. Washington University in St. Louis; Estados UnidosFil: Shady Lewis, Kristine E.. University of Kentucky; Estados UnidosFil: Feldman, Rebecca L.. Washington University in St. Louis; Estados UnidosFil: Hornbeck, Russ C.. Washington University in St. Louis; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Ances, Beau M.. Washington University in St. Louis; Estados UnidosFil: Berman, Sarah B.. University of Pittsburgh; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Brooks, William S.. Neuroscience Research Australia; Australia. University of New South Wales; AustraliaFil: Cash, David M.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Farlow, Martin R.. Indiana University; Estados UnidosFil: Fougère, Christian la. German Center for Neurodegenerative Diseases; Alemania. University Hospital of Tübingen; AlemaniaFil: Fox, Nick C.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Fulham, Michael J.. Royal Prince Alfred Hospital; Australia. University of Sydney; AustraliaFil: Jack, Clifford R.. Mayo Clinic; Estados UnidosFil: Joseph-Mathurin, Nelly. Washington University in St. Louis; Estados UnidosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Lee, Athene. University Brown; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; Alemania. Munich Cluster for Systems Neurology; AlemaniaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: McDade, Eric M.. Washington University in St. Louis; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Perrin, Richard J.. Washington University in St. Louis; Estados Unido

Prevalence and risk factors for human leptospirosis at a hospital serving a pastoralist community, Endulen, Tanzania

Background: Leptospirosis is suspected to be a major cause of illness in rural Tanzania associated with close contact with livestock. We sought to determine leptospirosis prevalence, identify infecting Leptospira serogroups, and investigate risk factors for leptospirosis in a rural area of Tanzania where pastoralist animal husbandry practices and sustained livestock contact are common. Methods: We enrolled participants at Endulen Hospital, Tanzania. Patients with a history of fever within 72 hours, or a tympanic temperature of ≥38.0°C were eligible. Serum samples were collected at presentation and 4–6 weeks later. Sera were tested using microscopic agglutination testing with 20 Leptospira serovars from 17 serogroups. Acute leptospirosis cases were defined by a ≥four-fold rise in antibody titre between acute and convalescent serum samples or a reciprocal titre ≥400 in either sample. Leptospira seropositivity was defined by a single reciprocal antibody titre ≥100 in either sample. We defined the predominant reactive serogroup as that with the highest titre. We explored risk factors for acute leptospirosis and Leptospira seropositivity using logistic regression modelling. Results: Of 229 participants, 99 (43.2%) were male and the median (range) age was 27 (0, 78) years. Participation in at least one animal husbandry practice was reported by 160 (69.9%). We identified 18 (7.9%) cases of acute leptospirosis, with Djasiman 8 (44.4%) and Australis 7 (38.9%) the most common predominant reactive serogroups. Overall, 69 (30.1%) participants were Leptospira seropositive and the most common predominant reactive serogroups were Icterohaemorrhagiae (n = 20, 29.0%), Djasiman (n = 19, 27.5%), and Australis (n = 17, 24.6%). Milking cattle (OR 6.27, 95% CI 2.24–7.52) was a risk factor for acute leptospirosis, and milking goats (OR 2.35, 95% CI 1.07–5.16) was a risk factor for Leptospira seropositivity. Conclusions: We identified leptospirosis in approximately one in twelve patients attending hospital with fever from this rural community. Interventions that reduce risks associated with milking livestock may reduce human infections

Intellectual enrichment and genetic modifiers of cognition and brain volume in Huntington's disease

An important step towards the development of treatments for cognitive impairment in ageing and neurodegenerative diseases is to identify genetic and environmental modifiers of cognitive function and understand the mechanism by which they exert an effect. In Huntington’s disease, the most common autosomal dominant dementia, a small number of studies have identified intellectual enrichment, i.e. a cognitively stimulating lifestyle and genetic polymorphisms as potential modifiers of cognitive function. The aim of our study was to further investigate the relationship and interaction between genetic factors and intellectual enrichment on cognitive function and brain atrophy in Huntington’s disease. For this purpose, we analysed data from Track-HD, a multi-centre longitudinal study in Huntington’s disease gene carriers and focused on the role of intellectual enrichment (estimated at baseline) and the genes FAN1, MSH3, BDNF, COMT and MAPT in predicting cognitive decline and brain atrophy. We found that carrying the 3a allele in the MSH3 gene had a positive effect on global cognitive function and brain atrophy in multiple cortical regions, such that 3a allele carriers had a slower rate of cognitive decline and atrophy compared with non-carriers, in agreement with its role in somatic instability. No other genetic predictor had a significant effect on cognitive function and the effect of MSH3 was independent of intellectual enrichment. Intellectual enrichment also had a positive effect on cognitive function; participants with higher intellectual enrichment, i.e. those who were better educated, had higher verbal intelligence and performed an occupation that was intellectually engaging, had better cognitive function overall, in agreement with previous studies in Huntington’s disease and other dementias. We also found that intellectual enrichment interacted with the BDNF gene, such that the positive effect of intellectual enrichment was greater in Met66 allele carriers than non-carriers. A similar relationship was also identified for changes in whole brain and caudate volume; the positive effect of intellectual enrichment was greater for Met66 allele carriers, rather than for non-carriers. In summary, our study provides additional evidence for the beneficial role of intellectual enrichment and carrying the 3a allele in MSH3 in cognitive function in Huntington’s disease and their effect on brain structure

Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): an epidemiological study.

BACKGROUND: Midlife hypertension confers increased risk for cognitive impairment in late life. The sensitive period for risk exposure and extent that risk is mediated through amyloid or vascular-related mechanisms are poorly understood. We aimed to identify if, and when, blood pressure or change in blood pressure during adulthood were associated with late-life brain structure, pathology, and cognition. METHODS: Participants were from Insight 46, a neuroscience substudy of the ongoing longitudinal Medical Research Council National Survey of Health and Development, a birth cohort that initially comprised 5362 individuals born throughout mainland Britain in one week in 1946. Participants aged 69-71 years received T1 and FLAIR volumetric MRI, florbetapir amyloid-PET imaging, and cognitive assessment at University College London (London, UK); all participants were dementia-free. Blood pressure measurements had been collected at ages 36, 43, 53, 60-64, and 69 years. We also calculated blood pressure change variables between ages. Primary outcome measures were white matter hyperintensity volume (WMHV) quantified from multimodal MRI using an automated method, amyloid-β positivity or negativity using a standardised uptake value ratio approach, whole-brain and hippocampal volumes quantified from 3D-T1 MRI, and a composite cognitive score-the Preclinical Alzheimer Cognitive Composite (PACC). We investigated associations between blood pressure and blood pressure changes at and between 36, 43, 53, 60-64, and 69 years of age with WMHV using generalised linear models with a gamma distribution and log link function, amyloid-β status using logistic regression, whole-brain volume and hippocampal volumes using linear regression, and PACC score using linear regression, with adjustment for potential confounders. FINDINGS: Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. 465 participants (238 [51%] men; mean age 70·7 years [SD 0·7]; 83 [18%] amyloid-β-positive) were included in imaging analyses. Higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) at age 53 years and greater increases in SBP and DBP between 43 and 53 years were positively associated with WMHV at 69-71 years of age (increase in mean WMHV per 10 mm Hg greater SBP 7%, 95% CI 1-14, p=0·024; increase in mean WMHV per 10 mm Hg greater DBP 15%, 4-27, p=0·0057; increase in mean WMHV per one SD change in SBP 15%, 3-29, p=0·012; increase in mean WMHV per 1 SD change in DBP 15%, 3-30, p=0·017). Higher DBP at 43 years of age was associated with smaller whole-brain volume at 69-71 years of age (-6·9 mL per 10 mm Hg greater DBP, -11·9 to -1·9, p=0·0068), as were greater increases in DBP between 36 and 43 years of age (-6·5 mL per 1 SD change, -11·1 to -1·9, p=0·0054). Greater increases in SBP between 36 and 43 years of age were associated with smaller hippocampal volumes at 69-71 years of age (-0·03 mL per 1 SD change, -0·06 to -0·001, p=0·043). Neither absolute blood pressure nor change in blood pressure predicted amyloid-β status or PACC score at 69-71 years of age. INTERPRETATION: High and increasing blood pressure from early adulthood into midlife seems to be associated with increased WMHV and smaller brain volumes at 69-71 years of age. We found no evidence that blood pressure affected cognition or cerebral amyloid-β load at this age. Blood pressure monitoring and interventions might need to start around 40 years of age to maximise late-life brain health. FUNDING: Alzheimer's Research UK, Medical Research Council, Dementias Platform UK, Wellcome Trust, Brain Research UK, Wolfson Foundation, Weston Brain Institute, Avid Radiopharmaceuticals

Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds

We investigate associations between normal-appearing white matter microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 birth cohort) underwent PET-MRI around age 70. Mean standardized normal-appearing white matter integrity metrics (fractional anisotropy, mean diffusivity, neurite density index and orientation dispersion index) were derived from diffusion MRI. Linear regression was used to test associations between normal-appearing white matter metrics and (i) concurrent measures, including whole brain volume, white matter hyperintensity volume, PET amyloid and cognition; (ii) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socio-economic position and genetic risk for Alzheimer's disease (APOE-ɛ4); (iii) systolic and diastolic blood pressure and cardiovascular health (Framingham Heart Study Cardiovascular Risk Score) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). Three hundred and sixty-two participants met inclusion criteria (mean age 70, 49% female). Higher white matter hyperintensity volume was associated with lower fractional anisotropy [b = -0.09 (95% confidence interval: -0.11, -0.06), P < 0.01], neurite density index [b = -0.17 (-0.22, -0.12), P < 0.01] and higher mean diffusivity [b = 0.14 (-0.10, -0.17), P < 0.01]; amyloid (in men) was associated with lower fractional anisotropy [b = -0.04 (-0.08, -0.01), P = 0.03)] and higher mean diffusivity [b = 0.06 (0.01, 0.11), P = 0.02]. Framingham Heart Study Cardiovascular Risk Score in later-life (age 69) was associated with normal-appearing white matter {lower fractional anisotropy [b = -0.06 (-0.09, -0.02) P < 0.01], neurite density index [b = -0.10 (-0.17, -0.03), P < 0.01] and higher mean diffusivity [b = 0.09 (0.04, 0.14), P < 0.01]}. Significant sex interactions (P < 0.05) emerged for midlife cardiovascular health (age 53) and normal-appearing white matter at 70: marginal effect plots demonstrated, in women only, normal-appearing white matter was associated with higher midlife Framingham Heart Study Cardiovascular Risk Score (lower fractional anisotropy and neurite density index), midlife systolic (lower fractional anisotropy, neurite density index and higher mean diffusivity) and diastolic (lower fractional anisotropy and neurite density index) blood pressure and greater blood pressure change between 43 and 53 years (lower fractional anisotropy and neurite density index), independently of white matter hyperintensity volume. In summary, poorer normal-appearing white matter microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how normal-appearing white matter can provide additional information to overt white matter disease. Our findings further show that greater 'midlife' cardiovascular risk and higher blood pressure were associated with poorer normal-appearing white matter microstructural integrity in females only, suggesting that women's brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health

Updating the study protocol: Insight 46 - a longitudinal neuroscience sub-study of the MRC National Survey of Health and Development - phases 2 and 3

BACKGROUND: Although age is the biggest known risk factor for dementia, there remains uncertainty about other factors over the life course that contribute to a person's risk for cognitive decline later in life. Furthermore, the pathological processes leading to dementia are not fully understood. The main goals of Insight 46-a multi-phase longitudinal observational study-are to collect detailed cognitive, neurological, physical, cardiovascular, and sensory data; to combine those data with genetic and life-course information collected from the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort); and thereby contribute to a better understanding of healthy ageing and dementia. METHODS/DESIGN: Phase 1 of Insight 46 (2015-2018) involved the recruitment of 502 members of the NSHD (median age = 70.7 years; 49% female) and has been described in detail by Lane and Parker et al. 2017. The present paper describes phase 2 (2018-2021) and phase 3 (2021-ongoing). Of the 502 phase 1 study members who were invited to a phase 2 research visit, 413 were willing to return for a clinic visit in London and 29 participated in a remote research assessment due to COVID-19 restrictions. Phase 3 aims to recruit 250 study members who previously participated in both phases 1 and 2 of Insight 46 (providing a third data time point) and 500 additional members of the NSHD who have not previously participated in Insight 46. DISCUSSION: The NSHD is the oldest and longest continuously running British birth cohort. Members of the NSHD are now at a critical point in their lives for us to investigate successful ageing and key age-related brain morbidities. Data collected from Insight 46 have the potential to greatly contribute to and impact the field of healthy ageing and dementia by combining unique life course data with longitudinal multiparametric clinical, imaging, and biomarker measurements. Further protocol enhancements are planned, including in-home sleep measurements and the engagement of participants through remote online cognitive testing. Data collected are and will continue to be made available to the scientific community

Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study.

BACKGROUND: A neuroimaging-based biomarker termed the brain age is thought to reflect variability in the brain's ageing process and predict longevity. Using Insight 46, a unique narrow-age birth cohort, we aimed to examine potential drivers and correlates of brain age. METHODS: Participants, born in a single week in 1946 in mainland Britain, have had 24 prospective waves of data collection to date, including MRI and amyloid PET imaging at approximately 70 years old. Using MRI data from a previously defined selection of this cohort, we derived brain-predicted age from an established machine-learning model (trained on 2001 healthy adults aged 18-90 years); subtracting this from chronological age (at time of assessment) gave the brain-predicted age difference (brain-PAD). We tested associations with data from early life, midlife, and late life, as well as rates of MRI-derived brain atrophy. FINDINGS: Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. We included 456 participants (225 female), with a mean chronological age of 70·7 years (SD 0·7; range 69·2 to 71·9). The mean brain-predicted age was 67·9 years (8·2, 46·3 to 94·3). Female sex was associated with a 5·4-year (95% CI 4·1 to 6·8) younger brain-PAD than male sex. An increase in brain-PAD was associated with increased cardiovascular risk at age 36 years (β=2·3 [95% CI 1·5 to 3·0]) and 69 years (β=2·6 [1·9 to 3·3]); increased cerebrovascular disease burden (1·9 [1·3 to 2·6]); lower cognitive performance (-1·3 [-2·4 to -0·2]); and increased serum neurofilament light concentration (1·2 [0·6 to 1·9]). Higher brain-PAD was associated with future hippocampal atrophy over the subsequent 2 years (0·003 mL/year [0·000 to 0·006] per 5-year increment in brain-PAD). Early-life factors did not relate to brain-PAD. Combining 12 metrics in a hierarchical partitioning model explained 33% of the variance in brain-PAD. INTERPRETATION: Brain-PAD was associated with cardiovascular risk, and imaging and biochemical markers of neurodegeneration. These findings support brain-PAD as an integrative summary metric of brain health, reflecting multiple contributions to pathological brain ageing, and which might have prognostic utility. FUNDING: Alzheimer's Research UK, Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association