Climate change modulates both energy demand and wind and solar energy supply but a globally synthetic analysis of supply–demand match (SDM) is lacking. Here, we use 12 state-of-the-art climate models to assess climate change impacts on SDM, quantified by the fraction of demand met by local wind or solar supply. For energy systems with varying dependence on wind or solar supply, up to 32% or 44% of non-Antarctic land areas, respectively, are projected to experience robust SDM reductions by the end of this century under an intermediate emission scenario. Smaller and more variable supply reduces SDM at northern middle-to-high latitudes, whereas reduced heating demand alleviates or reverses SDM reductions remarkably. By contrast, despite supply increases at low latitudes, raised cooling demand reduces SDM substantially. Changes in climate extremes and climate mean make size-comparable contributions. Our results provide early warnings for energy sectors in climate change adaptation.

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21–6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10⁻¹⁶), 6p21 (P = 2.3 × 10⁻¹⁴) and 15q25 (P = 2.2 × 10⁻⁶³). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16^INK4A/p14^ARF/CDKN2B/p15^INK4B/ANRIL; rs1333040, P = 3.0 × 10⁻⁷) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10⁻⁸). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer.

Low back pain (LBP) is a major health challenge globally. Research has identified common trajectories of pain over time. We aimed to investigate whether trajectories described in 1 primary care cohort can be confirmed in another, and to determine the prognostic value of factors collected 5 years prior to the identification of the trajectory. The study was conducted on 281 patients who had consulted primary care for LBP, at that point completed a baseline questionnaire, and then returned a questionnaire at 5-year follow-up plus at least 3 (of 6) subsequent monthly questionnaires. Baseline factors were measured using validated tools. Pain intensity scores from the 5-year follow-up and monthly questionnaires were used to assign participants into 4 previously derived pain trajectories (no or occasional mild, persistent mild, fluctuating, and persistent severe), using latent class analysis. Posterior probabilities of belonging to each cluster were estimated for each participant. The posterior probabilities for the assigned clusters were very high (>0.90) for each cluster except for the smallest “fluctuating” cluster (0.74). Lower social class and higher pain intensity were significantly associated with a more severe trajectory 5 years later, as were patients' perceptions of the greater consequences and longer duration of pain, and greater passive behavioural coping. Low back pain trajectories identified previously appear generalizable. These allow better understanding of the long-term course of LBP, and effective management tailored to individual trajectories needs to be identified.