Population Growth and Climate Change: A Dynamic Integrated Climate-Economy-Demography Model

We explore the bidirectional relationship between population growth and climate change: while population determines carbon emissions which drive climate change, climate change impacts the mortality rate and so population growth. Such population-climate feedback effects suggest that demographic policy may represent an alternative to traditional mitigation policies. We explore this possibility by introducing a population policy aiming at imposing a cap on population growth into an extended global integrated assessment model of climate-economy with endogenous fertility choices and temperature-related mortality. We show that the social costs of environmental policies, as reflected by both the social cost of carbon and social welfare, substantially increase by accounting for endogenous population change, but demographic policy allows to significantly reduce such costs. This clearly suggests that population growth does matter and so population policy may represent an effective mitigation tool to complement standard climate policies

Urban and non-urban contributions to the social cost of carbon

The social cost of carbon (SCC) serves as a concise gauge of climate change's economic impact, often reported at the global and country level. SCC values are disproportionately high for less-developed, populous countries. Assessing the contributions of urban and non-urban areas to the SCC can provide additional insights for climate policy. Cities are essential for defining global emissions, influencing warming levels and associated damages. High exposure and concurrent socioenvironmental problems exacerbate climate change risks in cities. Using a spatially explicit integrated assessment model, the SCC is estimated at USD$137-USD$579/tCO2, rising to USD$262-USD$1,075/tCO2 when including urban heat island (UHI) warming. Urban SCC dominates, with both urban exposure and the UHI contributing significantly. A permanent 1% reduction of the UHI in urban areas yields net present benefits of USD$484-USD$1,562 per urban dweller. Global cities have significant leverage and incentives for a swift transition to a low-carbon economy, and for reducing local warming

A Characterization of European Collective Action Initiatives and Their Role as Enablers of Citizens’ Participation in the Energy Transition

This paper provides novel additional evidence on the characteristics of Collective Action Initiatives (CAIs), investigating their role within the European energy sector. It analyses and presents results of a survey administered in six European countries: the Netherlands, Belgium, Italy, Poland, Estonia, and Spain. CAIs are studied in light of four key dimensions, those being their creation dynamics, the way they are organized, financed, and the activities they undertake. The results presented are also interpreted to reflect on their role as drivers of social innovation (SI) within energy transition in Europe. The analysis shows that the contribution of CAIs to the energy transition has a much wider scope than the development of energy projects and provision of energy services. CAIs are intrinsically socially innovative models of implementation as characterised by a strong level of citizen involvement and participation. Moreover, they have a potential multi-level role in the energy transition, from the technological and social perspectives. Indeed, alongside traditional energy activities, our results show that CAIs are evolving and expanding towards socially innovative activities, raising awareness on environmental issues, promoting citizens’ mobilization, and fostering social inclusion.This research was funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 837722, project COMETS (COllective action Models for Energy Transition and Social Innovation)

Molecular and pathological characterization of the EZH2 rs3757441 single nucleotide polymorphism in colorectal cancer

Background The enhancer of zeste-homolog 2 (EZH2) is involved in cancer development through gene silencing by trimethylation of lysine 27 of histone 3 (H3K27me3). The C/C genotype for the EZH2 rs3757441 single-nucleotide polymorphism (SNP) is linked with poor prognosis in metastatic colorectal cancer (CRC), but molecular and pathological characterization of this SNP is lacking. Methods 119 primary CRCs were analyzed. SNP was evaluated by real-time PCR from colonic healthy tissue, while EZH2 and H3K27me3 expression were studied by immunohistochemistry. We primarily looked for correlation between EZH2 rs3757441 genotypes and EZH2/H3K27me3 expression. Potential associations between EZH2/H3K27me3 expression and clinico-pathological features or KRAS exon 2 and BRAF exon 15 mutations were secondary endpoints. Statistical analysis was performed by chi-square test, T-test or ANOVA. Results The C/C genotype was significantly associated with higher EZH2 (100 vs. 44 %; P = 0.019) and H3K27me3 (100 vs. 38 %; P = 0.009) staining intensity compared with C/T and T/T. EZH2 3+ staining significantly correlated with stronger H3K27me3 expression (P = 0.039). KRAS and BRAF mutations were not associated with EZH2 or H3K27me3 expression. Conclusion EZH2 rs3757441 C/C genotype is associated with stronger EZH2 and H3K27me3 immunoreactivity in primary CRC: this SNP may serve as a promising biomarker for EZH2-targeting agents and may add independent information to KRAS and BRAF testing

Twelve Variants Polygenic Score for Low-Density Lipoprotein Cholesterol Distribution in a Large Cohort of Patients With Clinically Diagnosed Familial Hypercholesterolemia With or Without Causative Mutations

: Background A significant proportion of individuals clinically diagnosed with familial hypercholesterolemia (FH), but without any disease-causing mutation, are likely to have polygenic hypercholesterolemia. We evaluated the distribution of a polygenic risk score, consisting of 12 low-density lipoprotein cholesterol (LDL-C)-raising variants (polygenic LDL-C risk score), in subjects with a clinical diagnosis of FH. Methods and Results Within the Lipid Transport Disorders Italian Genetic Network (LIPIGEN) study, 875 patients who were FH-mutation positive (women, 54.75%; mean age, 42.47±15.00 years) and 644 patients who were FH-mutation negative (women, 54.21%; mean age, 49.73±13.54 years) were evaluated. Patients who were FH-mutation negative had lower mean levels of pretreatment LDL-C than patients who were FH-mutation positive (217.14±55.49 versus 270.52±68.59 mg/dL, P<0.0001). The mean value (±SD) of the polygenic LDL-C risk score was 1.00 (±0.18) in patients who were FH-mutation negative and 0.94 (±0.20) in patients who were FH-mutation positive (P<0.0001). In the receiver operating characteristic analysis, the area under the curve for recognizing subjects characterized by polygenic hypercholesterolemia was 0.59 (95% CI, 0.56-0.62), with sensitivity and specificity being 78% and 36%, respectively, at 0.905 as a cutoff value. Higher mean polygenic LDL-C risk score levels were observed among patients who were FH-mutation negative having pretreatment LDL-C levels in the range of 150 to 350 mg/dL (150-249 mg/dL: 1.01 versus 0.91, P<0.0001; 250-349 mg/dL: 1.02 versus 0.95, P=0.0001). A positive correlation between polygenic LDL-C risk score and pretreatment LDL-C levels was observed among patients with FH independently of the presence of causative mutations. Conclusions This analysis confirms the role of polymorphisms in modulating LDL-C levels, even in patients with genetically confirmed FH. More data are needed to support the use of the polygenic score in routine clinical practice

Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

: Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and Results An lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score ≥1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups &lt;0.0001); however, subjects with FH/M- and lp(a) score ≥1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level ≥190 mg/dL (or from 68% to 50%, considering a more conservative formula). Conclusions Our study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and ResultsAn lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score &gt;= 1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups &lt;0.0001); however, subjects with FH/M- and lp(a) score &gt;= 1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level &gt;= 190 mg/dL (or from 68% to 50%, considering a more conservative formula). ConclusionsOur study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

Balancing Climate Policies and Economic Development in the Mediterranean Countries

The goal of this work is to improve the spatial representation of the Regional Dynamic Integrated model of Climate and the Economy (RICE), in its ’99 version, focusing on the Mediterranean countries, while also updating the calibration to the base year 2015. We evaluate the impact of climate damages and temperature changes in several scenarios, drawing comparisons across regions. Thanks to the theoretical structure of the model, which considers energy as an explicit input factor, we examine macroeconomic and energy indicators across regions. We find that a general slow down in economic growth is needed to decrease emissions and keep temperature change within 2°C by the end of this century. Our results are embedded in a framework showing the costs of delaying the energy transition. Our figures relies on fossil-fuel inputs and exogenous energy saving improvements