Life Course Sleep Duration Trajectories and Risk and Age at Onset of Parkinson’s Disease

Life Course Sleep Duration Trajectories and Risk and Age at Onset of Parkinson’s Disease | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Life Course Sleep Duration Trajectories and Risk and Age at Onset of Parkinson’s Disease View ORCID Profile Yi Fang , Rebecca Hardy , Kristine Yaffe , Simon J. Little , Caroline M. Tanner , Yue Leng doi: https://doi.org/10.1101/2025.02.25.25322885 Yi Fang 1 Department of Psychiatry and Behavioral Sciences, University of California , San Francisco, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yi Fang Rebecca Hardy 2 School of Sport, Exercise, and Health Sciences, Loughborough University , Loughborough, UK PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kristine Yaffe 1 Department of Psychiatry and Behavioral Sciences, University of California , San Francisco, USA 3 Department of Epidemiology & Biostatistics and Department of Neurology, University of California , San Francisco, San Francisco, CA, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Simon J. Little 4 Movement Disorders and Neuromodulation Center, Department of Neurology, Weill Institute for Neuroscience, University of California , San Francisco, CA, USA MBBS, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Caroline M. Tanner 4 Movement Disorders and Neuromodulation Center, Department of Neurology, Weill Institute for Neuroscience, University of California , San Francisco, CA, USA MD, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yue Leng 1 Department of Psychiatry and Behavioral Sciences, University of California , San Francisco, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: Yue.Leng{at}ucsf.edu Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Importance Investigating associations between life course sleep duration and Parkinson’s disease (PD) may help clarify the role of sleep in early detection and/or prevention of PD. Objective To characterize life course sleep duration trajectories and their associations with PD risk and age at onset (AAO). Design Two ongoing online cohorts: Parkinson’s Progression Markers Initiative (PPMI)-Online (discovery; started in 2021) and Fox Insight (FI; validation; started in 2018). Setting Participants reported sleep duration across life stages, with PD-related follow-ups every three months. Participants A convenience sample of 5,660 individuals with PD and 10,245 without PD from PPMI-Online, and 1,929 participants with PD from FI. Exposures Self-reported sleep duration from ages 18 to 80+ in PPMI-Online and 12 to 66+ in FI. Latent class growth analysis (LCGA) identified sleep trajectories. Main Outcomes and Measures PD risk and AAO were assessed using logistic and linear regression, adjusting for demographics, lifestyle, comorbidities. Results The combined sample included 17,834 participants [age at sleep report 67.2±7.83 years; 9,735 (54.6%) female]. LCGA identified nine sleep trajectories in PPMI-Online, stable in early adulthood but diverging in midlife (stable, increasing, decreasing). Midlife sleep reductions (6-7 to ≤5-6 hours/day: OR = 1.90, 95% CI 1.61-2.24, P < .001; 7-8 to ≤6-7 hours/day: OR = 1.64, 95% CI 1.40-1.91, P < .001) and consistent short sleep (<=6 hours/day throughout adulthood: OR = 1.41, 95% CI 1.19-1.67, P < .001) demonstrated increased PD risk. Short sleep in early adulthood or midlife also had earlier AAO. The strongest effects were seen in those with ≤6 hours/day throughout adulthood (PPMI-Online: β = −2.45 years, 95% CI −3.33 to −1.56, P <.001) and those with a continuous decrease since adolescence (FI: β = −4.23 years, 95% CI −5.52 to −2.93, P < .001). These effects were independent of rapid eye movement sleep behavior disorders. Conclusions and Relevance Self-reported short sleep in early adulthood and midlife sleep reductions are associated with increased PD risk and earlier AAO. Self-perceived midlife sleep reduction may be a marker for future PD. Persons with chronic short sleep may be candidates for preventive intervention. Key Points Question: What is the relationship between life course sleep duration trajectories and the risk and age at onset of Parkinson’s disease (PD)? Findings: In this cohort study including 7,589 participants with PD and 10,245 without PD, short sleep duration in early adulthood or decreasing sleep duration after age 50 were associated with an increased risk and earlier age at onset of PD. Meaning: Short sleep duration over the life course, even in early adulthood (< 40 years), may contribute to risk of late-life PD; declining sleep duration after age 50 is a potential prodromal sign of PD. Introduction Sleep disturbances are common nonmotor symptoms of Parkinson’s disease (PD), affecting 60% to 90% of patients. 1 , 2 Evidence indicates a bidirectional relationship between PD and altered sleep, even before symptomatic onset. 3 , 4 Sleep deprivation exacerbates synucleinopathy in rodent models, 5 and poor sleep in human patients is associated with faster motor progression, 6 indicating the role of sleep disturbances in PD pathogenesis. Furthermore, PD pathology disrupts the sleep/wake neural circuitry before significant dopaminergic neuron loss. 3 This disruption is exemplified by rapid eye movement sleep behavioral disorder (RBD), a well-established prodromal marker of PD. 7 Population-based studies report higher rates of insomnia or hypersomnia, 8 – 10 and variations in sleep duration 11 , 12 preceding PD diagnosis. However, these studies typically focus on isolated time points, primarily the decade before diagnosis, overlooking potential life course changes in sleep duration. 13 Sleep trajectories have been associated with adverse neurological outcomes, such as dementia, 14 – 16 but no study has examined the association between life course sleep duration and PD. Given that prodromal PD can span decades 17 and early-life sleep patterns may contribute to neurodegeneration later in life, 18 it is crucial to investigate early-life sleep trajectories and their connection to PD onset. Such research is critical for disentangling the role of sleep disturbances as prodromal or risk factors for PD, offering opportunities for early detection and intervention. In this study, we identified self-reported sleep duration trajectories from adolesence to late adulthood using data from the Parkinson’s Progression Marker Initiative Online (PPMI-Online) and Fox Insight (FI). We assessed their relationship with PD risk and age at onset (AAO) in PPMI-Online, validating AAO findings in FI. We hypothesized that midlife sleep changes could serve as early markers of PD and that sleep durations below recommendations (<7 hours/night 19 , 20 ) in early adulthood or midlife would be associated with higher risk and earlier AAO of PD. Sensitivity analyses excluded participants with self-reported RBD, anxiety or depression, dementia, and examined sex as a potential effect modifier. Methods PPMI-Online and FI Study Design Both studies are ongoing longitudinal observational cohorts involving participants with and without PD. Convenience sampling was used to recruit participants aged 18 and older with minimal eligibility criteria. Recruitment was conducted through online channels, such as social media and email outreach, and on-site methods, including clinician referral and PD-related research events. Recruitment began in 2017 for FI 21 , 22 and 2021 for PPMI-Online. 23 Participants report PD status and symptoms quarterly via an online platform and complete occasional questionnaires, including those on sleep duration. The sleep questionnaire was administered during the 3rd and 15th months for PPMI-Online and between October 2017 and March 2019 for the FI study. For participants with multiple sleep reports, the most recent data were used for analysis. Study protocols were approved by institutional review boards (FI: New England IRB# 120160179; PPMI-Online: WCG IRB# 20211908), and all participants provided online informed consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Study Participants A flowchart of study participants is presented in Figure 1 . The final sample in the discovery cohort included 11,728 participants from PPMI-Online (5,660 with PD and 10,245 without PD). Among the latter, 6,922 had complete data and were classified as “probable prodromal PD (pPD)” (n = 1,104) or “no probable pPD” (n = 5,818) based on the Movement Disorders Society criteria 24 (80% probability cutoff 25 ; eMethods 1 ). The validation FI sample included 1,929 participants with PD; the 338 participants without PD were excluded due to limited sample size. Download figure Open in new tab Figure 1. Flow Diagram of Study Participants Abbreviations: PD = Parkinson’s disease, pPD = prodromal Parkinson’s disease For the current analysis, we applied identical exclusion criteria to both cohorts, including age at registration < 50 years, young-onset PD (AAO < 50 years 26 ), diagnosis changed during follow-up, missing age at diagnosis, reported age at diagnosis older than the participant’s current age, and all sleep duration responses marked as “prefer not to answer” or “don’t know”. Self-Perceived Sleep Duration Across the Lifespan Participants reported their typical sleep duration during current and prior age periods. Response options were categorical and included: less than 5 hours, 5-6 hours, 6-7 hours, 7-8 hours, more than 8 hours, don’t know, and prefer not to answer. Responses of “don’t know” or “prefer not to answer” were treated as missing values.The PPMI-Online study captured data spanning adulthood, with more granular age categories during late adulthood (18-29, 30-39, 40-49, 50-59, 60-64, 65-69, 70-74, 75-79, and 80 or older). The FI study focused on earlier life stages (12-17, 18-25, 26-35, 36-45, 46-55, 56-65, and 66 or older), capturing transitions from adolescence to adulthood. Outcome Measures PD status was self-reported at registration and follow-up, with previous studies confirming the reliability of self-reported PD in an online setting. 27 The self-reported age at first PD diagnosis was used as a proxy for PD AAO, as these measures were highly correlated. 28 Statistical Analysis We used latent class growth analysis (LCGA) to classify individuals into distinct sleep duration trajectory groups separately for PPMI-Online and FI, incorporating both linear and quadratic time components. LCGA identifies latent classes with similar trajectory patterns over time, assuming homogeneity within each class. 29 In the initial phase, we identified trajectory groups in participants with complete sleep duration data from ages 18-29 to 75-79 for PPMI-Online (n = 2,643) and ages 12-17 to 56-65 for FI (n = 1,668), with the midpoint of each age range approximating age. We excluded the ‘80 or older’ and ‘66 or older’ groups due to limited sample sizes and broad age ranges. Participants lacking sleep data for all required periods were excluded to avoid overrepresentation of younger groups and sparse data for older groups. Those who selected “prefer not to answer” or “not sure” for any age period were also excluded to avoid potential bias from recall errors. In the next phase, all participants with at least one valid data point were assigned to the trajectory class with the highest membership probability. To assess trajectory consistency and robustness, we visually compared trajectory groups from (1) participants with complete data across age periods (main analysis) versus all participants, (2) those with PD versus without PD, and (3) those with RBD symptoms/diagnoses versus those without RBD. We tested models with 1 to 9 classes, selecting the optimal model based on lower Bayesian Information Criteria (BIC) and interpretability. 30 BIC decreased as the number of classes increased from 1 to 9 for both PPMI-Online and FI. We selected the 9-class models for PPMI-Online and the 7-class model for FI, as additional classes showed similar patterns with no meaningful differences and limited sample size. Further LCGA details are provided in eMethods 2 . We analyzed associations between sleep duration trajectories and PD risk using logistic regression, and PD AAO using linear regression. Given possible non-monotonic changes during the prodromal phase, 31 , 32 we performed seperate binomial logistic regressions for “PD” (with “No PD” as the refrence) and “probable pPD” (with “no probable pPD” as the reference). We built three models: Model 1 (unadjusted), Model 2 (adjusted for age at sleep report [for risk analyses only], sex, race, family history of PD, education, and income), and Model 3 (further adjusted for history of anxiety, depression, brain injury, diabetes, hypertension; RBD Single-Question Screen 33 at the time of sleep report; lifetime caffeine intake, smoking status, and lifetime physical inactivity). We did not include age at sleep report as a covariate for AAO as AAO typically precedes the sleep report and is minimally influenced by the age at sleep report. Covariates, selected based on their known or suspected associations with sleep and PD, 34 were self-reported, with the closest report to sleep report used for repeated measures. All models met assumptions, with no variance inflation factor exceeding 5, indicating minimal multicollinearity. Sensitivity analyses included: (1) restricting to participants without self-reported RBD (n = 8395), given its association with shorter sleep, 35 (2) restricting to participants without history of anxiety or depression (n = 8566), given the divergent effects of these conditions and their treatments on sleep, (3) excluding participants with possible dementia (Penn Parkinson’s Daily Activities Questionnaire-15 < 43 36 ) to enhance recall accuracy (n = 14405), and (4) exploring sex as a possible effect modifier. Furthermore, as baseline sleep during early adulthood and trends during midlife are critical components of the sleep duration trajectories, we also investigated whether these two factors are independently associated with PD risk and AAO. We performed data analysis from January to December 2024 using R (version 4.3.2). Major packages included “lcmm” 37 (version 2.1.0), “stats” (version 4.3.2), “ggplot2” (version 3.4.4). All tests were 2-sided, with statistical significance set at P < .05. Results Study Participants Demographic and clinical characteristics of participants is summarized in Table 1 : 15,905 from PPMI-Online [mean age at sleep report: 67.2±7.94 years; 8,795 (55.3%) female; mean follow-up: 22.7±8.71 months] and 1,929 from FI [mean age at sleep report: 67.5±6.87 years; 940 (48.7%) female; mean follow-up: 68.1±10.1 months]. PD mean AAO was 65.3±7.57 in PPMI-Online and 62.9±6.96 in FI. In PPMI-Online, participants without PD were younger, more likely female, and had higher education, income, and positive PD family history compared to those with PD. Across subgroups (“no probable pPD,” “probable pPD,” and “PD”; eTable 1 ), motor and non-motor symptoms showed a clear progression, supporting the validity of the pPD criteria. View this table: View inline View popup Download powerpoint Table 1. Demographic and Clinical Characteristics of the Study Participants Sleep Duration Trajectories (PPMI-Online) PPMI-Online sleep duration trajectories ( Figure 2A ) remained relatively stable from the 20s to the 40s, with distinct trends emerging after the 50s (depicted in separate panels). Groups were labeled according to both baseline sleep in early adulthood (with categories: >8 hours, 7-8 hours, 6-7 hours, <=6 hours) and changes after age 50 (categorized as: stable, decrease, or increase). These trajectory shapes were largely consistent in sensitivity analyses. The “<=6 hrs stable” group had a lower age at sleep report, smaller percentage of White individuals, fewer years of education, and lower household income. Groups with changes after 50s (“7-8 hrs increase”, “6-7 hrs decrease”, “7-8 hrs decrease”) had higher age at sleep report and lower income. The “>8 hrs stable” group included more females ( eTable 2 ). Download figure Open in new tab Figure 2. Sleep Duration Trajectories Identified from PPMI-Online and Associations with Parkinson’s Disease Risk Abbreviations: PD = Parkinson’s disease, pPD = prodromal Parkinson’s disease Panel A: Sleep duration trajectory groups identified through latent class growth analysis, shown in separate panels based on trends emerging after age 50. Dots and shaded areas represent mean trajectories with 95% confidence intervals. The accompanying table shows the count and proportion of participants for each trajectory pattern. Panel B: Logistic regression results for the association between sleep duration trajectory patterns and risk of PD, using participants without a PD diagnosis as the reference group. Panel C: Logistic regression of sleep duration trajectory patterns and risk of “Probable pPD”, with the “No probable pPD” group as the reference. Model 1 was unadjusted. Model 2 adjusted for age at sleep report, sex, race, family history of PD, education, and income. Model 3 further adjusted for history of anxiety, depression, brain injury, diabetes, hypertension; Rapid Eye Movement Sleep Behavior Disorder Single-Question Screen at the time of sleep report; lifetime caffeine intake, smoking status, and lifetime physical inactivity. Sleep Duration Trajectories and PD Risk (PPMI-Online) Compared to the “7-8 hours stable” group, those with consistently shorter sleep (“<=6 hours stable”: OR = 1.41, 95% CI 1.19-1.67, P < .001, all ORs from Model 3) or decreasing sleep after age 50 (“6-7 hours decrease”: OR = 1.90, 95% CI 1.61-2.24, P < .001, “7-8 hours decrease”: OR = 1.64, 95% CI 1.40-1.91, P < .001) showed increased PD risk. The associations remained consistent across all adjustments ( Figure 2B ). The “6-7 hrs stable” group also showed a modestly higher risk of PD after adjustment (OR = 1.15, 95% CI 1.02-1.30, P = .02). For probable pPD, consistently shorter sleep (“<=6 hours stable”: OR = 1.61, 95% CI 1.10-2.32, P = .01) and decreasing sleep after 50 (“6-7 hours decrease”: OR = 1.94, 95% CI 1.35-2.77, P < .001; “7-8 hours decrease”: OR = 1.85, 95% CI 1.33-2.56, P < .001) were similarly associated with higher risks, consistent with the findings for PD risk. In addition, the “<=6 hrs increase” group also exhibited elevated pPD risk (OR = 1.73, 95% CI 1.12-2.62, P = .01). Sleep Duration Trajectories and PD AAO (PPMI-Online) Compared to the “7-8 hours stable” group, short sleep in early adulthood or decreasing sleep in midlife was associated with earlier PD AAO ( Figure 3 ). After full adjustment, the largest effect size was observed in the “<=6 hrs stable” group (β = −2.45 years, 95% CI −3.33 to −1.56, P = <.001) and “6-7 hrs decrease” group (β = −2.37 years, 95% CI −3.19 to −1.56, P = <.001), followed by the “<=6 hrs increase” (β = −1.73 years, 95% CI −2.85 to −0.62, P = .002) and “6-7 hrs stable” (β = −0.91 years, 95% CI −1.57 to −0.26, P = .006). Download figure Open in new tab Figure 3. Association of Life Course Sleep Duration with Age at Onset of Parkinson’s Disease in PPMI-Online Model 1 was unadjusted. Model 2 adjusted for sex, race, family history of PD, education, and income. Model 3 further adjusted for history of anxiety, depression, brain injury, diabetes, hypertension; Rapid Eye Movement Sleep Behavior Disorder Single-Question Screen at the time of sleep report; lifetime caffeine intake, smoking status, and lifetime physical inactivity. Sleep Duration Trajectories and Associations with PD AAO (FI) Most FI trajectories ( Figure 4A ) exhibited moderate sleep decline from adolescence to adulthood. Among them, four groups (labeled “>8 hours”, “7-8 hours”, “6-7 hours”, “<=6 hours”) maintained relatively stable during midlife. Two groups showed continuous declines: “decrease-1,” with decreases earlier in life, and “decrease-2,” with declines more evident during midlife. The “increase” group exhibited a sleep increase after the 40s, with early adulthood sleep duration between 6-7 hours, resembling the “6-7 hours increase” group in PPMI-Online. Groups with short sleep (“<=6 hrs”, “6-7 hrs”) and decreasing sleep (“decrease-1”, “decrease-2”) had lower education levels. The decrease groups also had a younger age at sleep report ( eTable 3 ). Download figure Open in new tab Figure 4. Sleep Duration Trajectories Identified from Fox Insight and Associations with Parkinson’s Disease Age at Onset Panel A: Dots and shaded areas represent mean trajectories for each class with 95% confidence intervals. The table displays the count and proportion of each trajectory pattern. Panel B: Sleep duration trajectory patterns and age at onset of PD. Model 1 was unadjusted. Model 2 adjusted for sex, race, family history of PD, education, and income. Model 3 further adjusted for history of anxiety, depression, brain injury, diabetes, hypertension; Rapid Eye Movement Sleep Behavior Disorder Single-Question Screen at the time of sleep report; lifetime caffeine intake, smoking status, and lifetime physical inactivity. Compared to the “7-8 hours” group, groups with less sleep exhibited earlier AAO ( Figure 4B ). The effect size was most pronounced in the decrease groups (“decrease-1”: β = −4.23 years, 95% CI −5.52 to −2.93, P < .001; “decrease-2” (β = −3.49 years, 95% CI −4.46 to −2.51, P < .001), followed by “<=6 hours” (β = −2.70 years, 95% CI −3.80 to −1.59, P < .001), “increase” (β = −1.65 years, 95% CI −3.04 to −0.26, P = .02), and “6-7 hours” (β = −1.37 years, 95% CI −2.16 to −0.57, P < .001). Sensitivity Analyses The associations remained consistent across sexes and were robust among participants without RBD symptoms or diagnoses throughout follow-up, those without a history of anxiety or depression, and after excluding individuals with possible dementia ( eFigure 1-6 ). Additionally, shorter baseline sleep duration and decreasing sleep during midlife were independently linked to an increased PD risk and earlierer AAO ( eFigure 7 ). Discussion In two large PD-centered online cohorts, we identified distinct self-reported life course sleep duration trajectories and examined their associations with PD risk and AAO. PPMI-Online results highlighted midlife, particularly around age 50, as a critical turning point in sleep duration. Declining sleep during midlife was associated with up to a 90% higher risk of PD and pPD. Chronic short sleep from early adulthood was associated with a 1.4-fold increased PD risk. Additionally, both PPMI-Online and FI cohorts indicated that shorter-than-recommended sleep in early adulthood or midlife was associated with an earlier AAO, with such patterns associated with earlier AAO by up to 2.5 to 4.2 years. Due to the different life stage focuses, PPMI-Online and FI trajectories exhibited complementary patterns. Around 50% of PPMI-Online participants were in trajectory groups showing changes after age 50, and 60% of FI participants belong to groups showing declines from adolescence to the 30s. These findings align with previously identified turning points in sleep duration at ages 33 and 53. 13 However, stable groups might be overestimated due to categorical presentation, potentially missing subtle changes. Midlife (ages 40s to 60s) is increasingly recognized as a critical period marked by accelerated declines in gene expressions, brain connectivity, and cognitive function. 38 , 39 We observed that decreasing sleep after age 50 was associated with increased PD and pPD risk, suggesting that declining sleep is evident in prodromal PD and continues into clinical PD. This association remained robust even among participants without self-reported RBD, anxiety, or depression, indicating that decreasing sleep may be an early manifestation of PD itself, rather than a consequence of common prediagnostic comorbidities observed in a subset of patients. 40 Conversely, the “≤6 hrs increase” group showed an increased risk of pPD but not PD, suggesting that increasing sleep during midlife, particularly after chronic short sleep, may indicate prodromal PD. However, our study lacked an ultra-long sleep group (>8 hours/day), limiting comparisons to previous reports linking >=9 hours/day with higher PD risk. 41 , 42 Given the long prodromal window, it is challenging to determine the direction of the relationship between sleep disturbances and PD. Our study indicates that short sleep in early adulthood or midlife is associated with increased risk and earlier AAO of PD, potentially preceding the onset of PD by up to five decades. These findings suggest that chronic short sleep might be a risk factor, with prolonged short sleep likely preceding neurodegeneration. Our results also underscore the public health relevance of addressing insufficient sleep, particularly in minoritized populations, 43 and its adverse effects on aging-related outcomes. 44 As preventive trials for PD are being planned, 45 promoting healthy sleep hygiene may represent a scalable strategy for reducing risk or delaying onset. Our findings align with mechanistic evidence from animal and human studies. Sleep disturbances may arise from early PD pathology affecting the locus coeruleus, 46 hypothalamus, 47 and dopaminergic systems. 48 Conversely, sleep deprivation exacerbates synucleinopathy, 5 possibly through mitochondrial and oxidative stress, 49 neuroinflammation, 50 impaired glymphatic clearance, 51 and synaptic homeostasis. 52 Notably, the locus coeruleus is particularly vulnerable to insufficient sleep and may contribute to PD pathogenesis. 53 , 54 Furthermore, chronic sleep loss in young adult rodents has long-lasting neurological effects 55 and is associated with neurodegeneration later in life, 18 supporting our findings that short sleep in early adulthood might contribute to PD in later years. This study leveraged two online PD-centered cohorts, providing a cost-efficient framework with a large participant pool and longitudinal sleep duration data spanning adolescence to age 80. However, several limitations should be considered. First, the retrospective self-reported sleep duration may introduce recall bias, although evidence suggests such information can be accurate. 56 , 57 Self-reported sleep duration modestly correlates with objectively measured sleep. 58 In this study, participants could select “don’t know” for uncertain responses, and results remained robust after excluding possible dementia. Additionally, the sleep trajectory turning points aligned with a previous large-scale study, 13 enhancing the credibility of self-reported sleep. Even if discrepancies exist, self-perceived decline in sleep after midlife may still serve as a valuable indicator of PD risk. Second, pPD was determined by self-reported markers, without clinical evaluation or synuclein-based biomarkers. Furthermore, the study population was predominantly White, with high socioeconomic status and education, and participants without PD were enriched for PD risk factors. Further studies are needed to assess generalizability. Finally, while the findings suggest short sleep as a potential PD risk factor, the observational nature of this study limits causal inferences. Conclusion In this large-scale study involving individuals with and without PD, we found that the 50s represent a significant turning point in sleep duration. Monitoring sleep duration changes, particularly after age 50, is crucial, as declining sleep duration at this stage may signal a higher risk and earlier onset of PD. Additionally, chronic short sleep was associated with an increased risk and earlier AAO of PD, suggesting short sleep as a potential risk factor and intervention targets. Data Availability All data produced are available online at www.ppmi-info.org and https://foxinsightinfo.michaeljfox.org/insight/explore/insight.jsp https://www.ppmi-info.org https://foxden.michaeljfox.org/insight/explore/insight.jsp Data Sharing Statement Final data used in this article were obtained from the PPMI study (tier1 data downloaded on 03 July 2024, https://www.ppmi-info.org/access-data-specimens/download-data , RRID:SCR_006431) and the FI study (version: December 2024 archived monthly data, https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp ). For up-todate information on the PPMI study, visit www.ppmi-info.org . For up-to-date information on the FI study, visit https://foxinsightinfo.michaeljfox.org/insight/explore/insight.jsp . Acknowledgement We would like to thank the Parkinson’s community for participating in the Fox Insight and PPMI-Online study to make this research possible. The Fox Insight Study is funded by The Michael J. Fox Foundation for Parkinson’s Research. PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including 4D Pharma, Abbvie, AcureX, Allergan, Amathus Therapeutics, Aligning Science Across Parkinson’s, AskBio, Avid Radiopharmaceuticals, BIAL, Biogen, Biohaven, BioLegend, BlueRock Therapeutics, Bristol-Myers Squibb, Calico Labs, Celgene, Cerevel Therapeutics, Coave Therapeutics, DaCapo Brainscience, Denali, Edmond J. Safra Foundation, Eli Lilly, Gain Therapeutics, GE HealthCare, Genentech, GSK, Golub Capital, Handl Therapeutics, Insitro, Janssen Neuroscience, Lundbeck, Merck, Meso Scale Discovery, Mission Therapeutics, Neurocrine Biosciences, Pfizer, Piramal, Prevail Therapeutics, Roche, Sanofi, Servier, Sun Pharma Advanced Research Company, Takeda, Teva, UCB, Vanqua Bio, Verily, Voyager Therapeutics, the Weston Family Foundation and Yumanity Therapeutics. References 1. ↵ Lajoie AC , Lafontaine AL , Kaminska M . 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